forked from Selig/openclaw-skill
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12
ProjectManager/README.md
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12
ProjectManager/README.md
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# OpenClaw Project Package
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此資料夾為可直接匯入或參考的原始檔案結構，包含：
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- `skills/`：5 個 OpenClaw skills
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- `rules/`：附件、文件編號、SOP、工作記錄模板
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- `dashboards/`：專案總覽
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- `projects/`：2 個主專案的 `project.yaml`
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## 主專案
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- `P-ONLINE-DOC-AGENT`
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- `P-ETL-VISUAL-PLATFORM`
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30
ProjectManager/dashboards/projects-overview.md
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ProjectManager/dashboards/projects-overview.md
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# Projects Overview
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## 主專案總覽
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| Project ID | 名稱 | 狀態 | 進度 | 下一步 |
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|---|---|---:|---:|---|
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| P-ONLINE-DOC-AGENT | Agent 操作線上文件系統 | active | 25% | 建立 EFLOW 附件規則 |
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| P-ETL-VISUAL-PLATFORM | ETL 資料庫轉換可視化網頁 | active | 35% | 建立 SP 與目標欄位 mapping v1 |
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## 子專案總覽
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### P-ONLINE-DOC-AGENT
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| Subproject ID | 名稱 | 狀態 | 備註 |
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|---|---|---|---|
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| SP-OFFICIAL-DOC | 線上公文操作 | doing | 建立 SOP v1 |
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| SP-EFLOW | EFLOW 操作 | doing | 整理送件與附件流程 |
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| SP-FORMBUILD | FORMBUILD 操作 | todo | 尚待蒐集畫面與欄位 |
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| SP-ATTACHMENT-RULES | 附件規則 | doing | 定義資料夾與命名 |
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| SP-DOC-ID-RULES | 文件編號規則 | todo | 定義 CASE 與系統編號 |
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### P-ETL-VISUAL-PLATFORM
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| Subproject ID | 名稱 | 狀態 | 備註 |
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|---|---|---|---|
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| SP-ETL-PIPELINE | ETL 流程整理 | doing | 蒐集流程與來源資料 |
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| SP-DB-SP-ANALYSIS | SP 分析 | doing | 匯整 SP 清單 |
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| SP-TARGET-FIELD-MAPPING | 目標欄位 mapping | todo | 建立欄位對照表 |
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| SP-LLM-DIFF-CHECK | LLM 差異比對 | todo | 定義比較規則 |
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| SP-VISUAL-WEB | 可視化頁面 | todo | 定義顯示模組 |
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13
ProjectManager/projects/P-ETL-VISUAL-PLATFORM/project.yaml
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ProjectManager/projects/P-ETL-VISUAL-PLATFORM/project.yaml
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project_id: P-ETL-VISUAL-PLATFORM
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name: ETL 資料庫轉換可視化網頁
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status: active
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objective: >-
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建立 ETL 資料庫轉換可視化網頁，並以 LLM 協助比對 Stored Procedure 與目標文件欄位差異。
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current_phase: analysis
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next_action: 建立 SP 與目標欄位 mapping 表 v1
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subprojects:
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- SP-ETL-PIPELINE
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- SP-DB-SP-ANALYSIS
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- SP-TARGET-FIELD-MAPPING
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- SP-LLM-DIFF-CHECK
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- SP-VISUAL-WEB
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14
ProjectManager/projects/P-ONLINE-DOC-AGENT/project.yaml
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ProjectManager/projects/P-ONLINE-DOC-AGENT/project.yaml
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project_id: P-ONLINE-DOC-AGENT
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name: Agent 操作線上文件系統
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status: active
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objective: >-
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建立一套可由 Agent 依 SOP 操作的線上文件流程，涵蓋線上公文、EFLOW、FORMBUILD，
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並整合附件規則、文件編號規則與工作記錄。
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current_phase: definition
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next_action: 建立 EFLOW 附件規則與操作步驟 v1
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subprojects:
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- SP-OFFICIAL-DOC
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- SP-EFLOW
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- SP-FORMBUILD
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- SP-ATTACHMENT-RULES
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- SP-DOC-ID-RULES
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27
ProjectManager/rules/attachment-filing-rules.md
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ProjectManager/rules/attachment-filing-rules.md
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# 附件歸檔規則
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## 目錄結構
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```text
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attachments/
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official-doc/
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DOC-YYYY-NNN/
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eflow/
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EFL-YYYY-NNN/
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formbuild/
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FBD-YYYY-NNN/
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```
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## 檔名格式
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`[文件編號]_[附件類型]_[版本]_[日期].[副檔名]`
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### 範例
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- `DOC-2026-001_申請書_v1_2026-03-12.pdf`
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- `EFL-2026-003_核准函_v2_2026-03-12.pdf`
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## Agent 上傳前檢查
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- 是否有文件編號
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- 是否放在正確資料夾
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- 檔名是否正確
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- 版本是否正確
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- 是否缺少必要附件
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20
ProjectManager/rules/doc-id-convention.md
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ProjectManager/rules/doc-id-convention.md
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# 文件編號規則
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## 系統文件編號
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- 線上公文：`DOC-YYYY-NNN`
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- EFLOW：`EFL-YYYY-NNN`
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- FORMBUILD：`FBD-YYYY-NNN`
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## 跨系統案件編號
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- `CASE-YYYY-NNN`
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## 範例
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- `CASE-2026-015`
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- `DOC-2026-021`
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- `EFL-2026-009`
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## 規則
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1. 新建文件前先判斷系統類型
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2. 若屬同一案件，優先掛既有 CASE-ID
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3. 所有附件檔名必須以前述文件編號開頭
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4. 文件記錄中需保留 CASE 與系統文件編號的對應
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40
ProjectManager/rules/web-operation-sop.md
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ProjectManager/rules/web-operation-sop.md
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# Web Operation SOP Template
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## 系統名稱
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- 線上公文 / EFLOW / FORMBUILD
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## 操作目的
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- 例如：建立新案件、送件、補附件、更新欄位
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## 前置資料
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- 帳號/登入條件
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- 文件編號
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- CASE-ID（若有）
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- 附件清單
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- 欄位資料
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## 操作步驟
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1. 進入系統
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2. 開啟目標頁面
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3. 輸入或確認必要欄位
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4. 上傳附件
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5. 執行送出或儲存
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6. 確認結果
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## 上傳附件檢查
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- 路徑：
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- 檔名：
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- 版本：
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- 是否齊全：
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## 結果記錄
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- 成功 / 失敗 / 阻塞
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- 畫面狀態
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- 文件編號
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- 下一步
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## 常見錯誤
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- 登入失敗
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- 欄位缺漏
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- 附件格式不符
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- 權限不足
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25
ProjectManager/rules/worklog-format.md
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ProjectManager/rules/worklog-format.md
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# Worklog Format
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## 日期
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- YYYY-MM-DD
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## 所屬主專案
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- P-ONLINE-DOC-AGENT / P-ETL-VISUAL-PLATFORM
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## 所屬子專案
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- 例如：SP-EFLOW
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## 本次完成
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-
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## 本次阻塞
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-
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## 使用文件 / 附件
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-
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## 文件編號 / CASE-ID
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-
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## 下一步
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-
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62
ProjectManager/skills/attachment-filing-rules/SKILL.md
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62
ProjectManager/skills/attachment-filing-rules/SKILL.md
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---
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name: attachment-filing-rules
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description: 用於規範不同線上系統所需附件的資料夾放置、命名、版本與 Agent 取用方式。
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---
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# Purpose
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本 skill 用來統一附件管理，讓 Agent 能穩定找到正確檔案並完成上傳。
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# Scope
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適用系統：
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- 線上公文
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- EFLOW
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- FORMBUILD
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# Folder Structure
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```text
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attachments/
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official-doc/
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DOC-YYYY-NNN/
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eflow/
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EFL-YYYY-NNN/
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formbuild/
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FBD-YYYY-NNN/
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```
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# File Naming Convention
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格式：
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`[文件編號]_[附件類型]_[版本]_[日期].[副檔名]`
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|
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範例：
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- `DOC-2026-001_申請書_v1_2026-03-12.pdf`
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- `EFL-2026-003_核准函_v2_2026-03-12.pdf`
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- `FBD-2026-007_附件清單_v1_2026-03-12.xlsx`
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# Rules
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## 1. 上傳前檢查
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Agent 上傳附件前必須確認：
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1. 有文件編號
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2. 位於正確系統資料夾
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3. 檔名格式正確
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4. 版本號正確
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5. 是最新檔案
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6. 必要附件已齊全
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## 2. 禁止事項
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- 不可上傳檔名不明或臨時檔
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- 不可上傳無版本資訊之重複檔案
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- 不可跨系統誤用資料夾中的附件
|
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## 3. 回應格式
|
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當被要求尋找或準備附件時，回應：
|
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- 系統類型
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- 文件編號
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- 預期附件類型
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- 建議資料夾路徑
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- 檔名檢查結果
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- 缺漏項目
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54
ProjectManager/skills/doc-id-convention/SKILL.md
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54
ProjectManager/skills/doc-id-convention/SKILL.md
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---
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name: doc-id-convention
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description: 用於規範線上公文、EFLOW、FORMBUILD 的文件編號與跨系統案件識別方式。
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---
|
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# Purpose
|
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|
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本 skill 用來讓文件、附件、案件、流程之間能一致對應。
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# ID Types
|
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|
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## 1. 系統文件編號
|
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|
- 線上公文：`DOC-YYYY-NNN`
|
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|
- EFLOW：`EFL-YYYY-NNN`
|
||||||
|
- FORMBUILD：`FBD-YYYY-NNN`
|
||||||
|
|
||||||
|
範例：
|
||||||
|
- `DOC-2026-001`
|
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|
- `EFL-2026-014`
|
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|
- `FBD-2026-007`
|
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|
|
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|
## 2. 案件編號（跨系統）
|
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|
若同一件事情會跨多個系統，建立案件編號：
|
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|
- `CASE-YYYY-NNN`
|
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|
|
||||||
|
範例：
|
||||||
|
- `CASE-2026-015`
|
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|
- `DOC-2026-021`
|
||||||
|
- `EFL-2026-009`
|
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|
|
||||||
|
# Rules
|
||||||
|
|
||||||
|
## 1. 新建文件
|
||||||
|
- 先判斷系統類型
|
||||||
|
- 分配對應前綴編號
|
||||||
|
- 確認是否屬於既有 CASE
|
||||||
|
|
||||||
|
## 2. 附件命名
|
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|
所有附件檔名必須以前述文件編號開頭。
|
||||||
|
|
||||||
|
## 3. 記錄關聯
|
||||||
|
若文件跨系統，必須明確記錄：
|
||||||
|
- CASE-ID
|
||||||
|
- 各系統文件編號
|
||||||
|
- 關聯說明
|
||||||
|
|
||||||
|
# Response Format
|
||||||
|
|
||||||
|
當需要建立或查詢文件編號時，輸出：
|
||||||
|
- 系統類型
|
||||||
|
- 是否已有 CASE-ID
|
||||||
|
- 建議文件編號
|
||||||
|
- 關聯文件
|
||||||
|
- 建議資料夾名稱
|
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76
ProjectManager/skills/etl-visual-project/SKILL.md
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76
ProjectManager/skills/etl-visual-project/SKILL.md
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---
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name: etl-visual-project
|
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|
description: 用於管理 ETL 資料庫轉換可視化網頁專案，並包含 SP 分析、目標欄位 mapping 與 LLM 差異比對。
|
||||||
|
---
|
||||||
|
|
||||||
|
# Purpose
|
||||||
|
|
||||||
|
此 skill 用於處理：
|
||||||
|
- ETL 資料流程整理
|
||||||
|
- Stored Procedure 分析
|
||||||
|
- 目標文件欄位 mapping
|
||||||
|
- LLM 比較 SP 與目標欄位差異
|
||||||
|
- 可視化網頁的需求與模組規劃
|
||||||
|
|
||||||
|
# Project
|
||||||
|
|
||||||
|
主專案：
|
||||||
|
`P-ETL-VISUAL-PLATFORM`
|
||||||
|
|
||||||
|
子專案：
|
||||||
|
- `SP-ETL-PIPELINE`
|
||||||
|
- `SP-DB-SP-ANALYSIS`
|
||||||
|
- `SP-TARGET-FIELD-MAPPING`
|
||||||
|
- `SP-LLM-DIFF-CHECK`
|
||||||
|
- `SP-VISUAL-WEB`
|
||||||
|
|
||||||
|
# Core Objective
|
||||||
|
|
||||||
|
建立一套能呈現 ETL 資料庫轉換流程的可視化網頁。
|
||||||
|
|
||||||
|
# Branch Objective
|
||||||
|
|
||||||
|
使用 LLM 比較：
|
||||||
|
- Stored Procedure 輸出或邏輯
|
||||||
|
- 目標文件定義的欄位
|
||||||
|
- 欄位差異與缺漏
|
||||||
|
- 型別差異
|
||||||
|
- 命名差異
|
||||||
|
- 規則差異
|
||||||
|
|
||||||
|
# Workflow
|
||||||
|
|
||||||
|
## 1. 資料蒐集
|
||||||
|
- 蒐集 SP 清單
|
||||||
|
- 蒐集目標文件欄位定義
|
||||||
|
- 蒐集資料表與 ETL 流向
|
||||||
|
|
||||||
|
## 2. Mapping
|
||||||
|
- 建立欄位對照表
|
||||||
|
- 標記來源欄位、目標欄位、轉換規則
|
||||||
|
|
||||||
|
## 3. LLM Diff Check
|
||||||
|
- 比較 SP 欄位與目標文件欄位
|
||||||
|
- 輸出缺漏、命名不一致、型別不一致
|
||||||
|
|
||||||
|
## 4. Visual Web
|
||||||
|
- 定義頁面模組
|
||||||
|
- 呈現流程圖、欄位 mapping、差異報表
|
||||||
|
|
||||||
|
# Standard Output
|
||||||
|
|
||||||
|
每次回應時，輸出：
|
||||||
|
1. 所屬子專案
|
||||||
|
2. 本次目標
|
||||||
|
3. 所需輸入資料
|
||||||
|
4. 產出物
|
||||||
|
5. 差異或阻塞
|
||||||
|
6. 下一步
|
||||||
|
|
||||||
|
# Example Tasks
|
||||||
|
|
||||||
|
- 匯出 SP 欄位清單
|
||||||
|
- 建立目標文件欄位表
|
||||||
|
- 建立 mapping 表 v1
|
||||||
|
- 用 LLM 產出欄位差異報告
|
||||||
|
- 設計 ETL 可視化頁面需求草稿
|
||||||
88
ProjectManager/skills/online-doc-agent-ops/SKILL.md
Normal file
88
ProjectManager/skills/online-doc-agent-ops/SKILL.md
Normal file
@@ -0,0 +1,88 @@
|
|||||||
|
---
|
||||||
|
name: online-doc-agent-ops
|
||||||
|
description: 用於協助 Agent 操作線上文件系統，包括線上公文、EFLOW、FORMBUILD，並依 SOP、附件規則、文件編號規則執行。
|
||||||
|
---
|
||||||
|
|
||||||
|
# Purpose
|
||||||
|
|
||||||
|
此 skill 用於管理與執行以下系統的 Agent 操作：
|
||||||
|
- 線上公文
|
||||||
|
- EFLOW
|
||||||
|
- FORMBUILD
|
||||||
|
|
||||||
|
# Supported Scope
|
||||||
|
|
||||||
|
## 主專案
|
||||||
|
`P-ONLINE-DOC-AGENT`
|
||||||
|
|
||||||
|
## 子專案
|
||||||
|
- `SP-OFFICIAL-DOC`
|
||||||
|
- `SP-EFLOW`
|
||||||
|
- `SP-FORMBUILD`
|
||||||
|
- `SP-ATTACHMENT-RULES`
|
||||||
|
- `SP-DOC-ID-RULES`
|
||||||
|
|
||||||
|
# Execution Rules
|
||||||
|
|
||||||
|
## 1. 操作前必做檢查
|
||||||
|
|
||||||
|
每次操作前，先確認：
|
||||||
|
1. 目標系統是什麼
|
||||||
|
2. 這次操作的目的為何
|
||||||
|
3. 是否需要附件
|
||||||
|
4. 是否已有文件編號
|
||||||
|
5. 是否需要建立操作記錄
|
||||||
|
|
||||||
|
## 2. 系統判斷
|
||||||
|
|
||||||
|
### 線上公文
|
||||||
|
適用於：公文建立、上傳、送簽、帶附件等流程
|
||||||
|
|
||||||
|
### EFLOW
|
||||||
|
適用於：流程送件、附件上傳、流程狀態追蹤等
|
||||||
|
|
||||||
|
### FORMBUILD
|
||||||
|
適用於：表單填寫、欄位輸入、附件上傳、資料提交等
|
||||||
|
|
||||||
|
## 3. 附件處理規則
|
||||||
|
|
||||||
|
若系統需要附件：
|
||||||
|
- 先取得文件編號
|
||||||
|
- 依系統類型到指定資料夾找檔案
|
||||||
|
- 驗證檔名是否符合規則
|
||||||
|
- 驗證是否為最新版本
|
||||||
|
- 驗證附件是否齊全
|
||||||
|
|
||||||
|
## 4. 操作輸出
|
||||||
|
|
||||||
|
每次完成操作後，至少記錄：
|
||||||
|
- 日期時間
|
||||||
|
- 操作系統
|
||||||
|
- 文件編號
|
||||||
|
- 操作目的
|
||||||
|
- 使用附件
|
||||||
|
- 結果（成功 / 失敗 / 阻塞）
|
||||||
|
- 下一步
|
||||||
|
|
||||||
|
# Standard Response Format
|
||||||
|
|
||||||
|
當使用此 skill 時，請依下列格式回應：
|
||||||
|
|
||||||
|
1. 系統名稱
|
||||||
|
2. 本次操作目的
|
||||||
|
3. 需要的前置資料
|
||||||
|
4. 執行步驟
|
||||||
|
5. 附件檢查
|
||||||
|
6. 完成後記錄
|
||||||
|
7. 可能錯誤與處理方式
|
||||||
|
|
||||||
|
# Subsystem Notes
|
||||||
|
|
||||||
|
## SP-OFFICIAL-DOC
|
||||||
|
重點：公文流程、附件、送件狀態
|
||||||
|
|
||||||
|
## SP-EFLOW
|
||||||
|
重點：流程節點、附件、送件前檢查
|
||||||
|
|
||||||
|
## SP-FORMBUILD
|
||||||
|
重點：表單欄位、填寫規則、送出驗證
|
||||||
98
ProjectManager/skills/project-governance/SKILL.md
Normal file
98
ProjectManager/skills/project-governance/SKILL.md
Normal file
@@ -0,0 +1,98 @@
|
|||||||
|
---
|
||||||
|
name: project-governance
|
||||||
|
description: 用於判斷新工作應歸屬哪個主專案、子專案或共用規則，並維持專案、子專案、任務、規則四個層級的邊界清楚。
|
||||||
|
---
|
||||||
|
|
||||||
|
# Purpose
|
||||||
|
|
||||||
|
此 skill 用來避免將「類別、專案、子專案、任務」混淆。
|
||||||
|
|
||||||
|
適用於以下情境：
|
||||||
|
- 使用者提出新的工作、想法或需求
|
||||||
|
- 需要判斷是否建立新專案或新子專案
|
||||||
|
- 需要把任務正確掛到既有專案
|
||||||
|
- 需要判斷某件事是共用規則，而不是專案內容
|
||||||
|
|
||||||
|
# Core Rules
|
||||||
|
|
||||||
|
## 1. 四層模型
|
||||||
|
|
||||||
|
1. 規則（Rules）
|
||||||
|
- 共用命名規範
|
||||||
|
- 文件編號規則
|
||||||
|
- 附件歸檔規則
|
||||||
|
- SOP 與記錄格式
|
||||||
|
|
||||||
|
2. 主專案（Projects）
|
||||||
|
- `P-ONLINE-DOC-AGENT`
|
||||||
|
- `P-ETL-VISUAL-PLATFORM`
|
||||||
|
|
||||||
|
3. 子專案（Subprojects）
|
||||||
|
- 某主專案下的模組、工作流、系統分支
|
||||||
|
|
||||||
|
4. 任務（Tasks）
|
||||||
|
- 可執行、可完成、可驗收的最小工作單位
|
||||||
|
|
||||||
|
## 2. 分類判斷規則
|
||||||
|
|
||||||
|
當收到新工作時，依序判斷：
|
||||||
|
|
||||||
|
### A. 這是共用規則嗎？
|
||||||
|
若是關於以下內容，歸入 Rules：
|
||||||
|
- 附件資料夾如何放
|
||||||
|
- 文件怎麼編號
|
||||||
|
- Agent 如何記錄工作
|
||||||
|
- 線上操作 SOP 的共同格式
|
||||||
|
|
||||||
|
### B. 這是屬於哪個主專案？
|
||||||
|
- 若與線上公文、EFLOW、FORMBUILD 的操作、自動化、附件、送件流程有關，歸入 `P-ONLINE-DOC-AGENT`
|
||||||
|
- 若與 ETL、Stored Procedure、欄位 mapping、LLM 比對、資料轉換可視化頁面有關，歸入 `P-ETL-VISUAL-PLATFORM`
|
||||||
|
|
||||||
|
### C. 是否應建立子專案？
|
||||||
|
符合以下任一條件時，建立子專案：
|
||||||
|
- 有獨立系統或獨立頁面
|
||||||
|
- 有獨立流程或 SOP
|
||||||
|
- 有獨立輸入輸出或文件產出
|
||||||
|
- 有明顯可拆分的技術模組
|
||||||
|
|
||||||
|
### D. 是否只是任務？
|
||||||
|
若該工作可在單次工作期內完成，且有明確完成條件，則建立為任務，不建立子專案。
|
||||||
|
|
||||||
|
# Required Output Format
|
||||||
|
|
||||||
|
在分析新工作時，固定輸出：
|
||||||
|
|
||||||
|
1. 歸屬層級：Rule / Project / Subproject / Task
|
||||||
|
2. 所屬主專案
|
||||||
|
3. 所屬子專案（若有）
|
||||||
|
4. 建議任務名稱
|
||||||
|
5. 下一步最小可執行動作
|
||||||
|
6. 是否需要寫入工作記錄
|
||||||
|
|
||||||
|
# Examples
|
||||||
|
|
||||||
|
## Example 1
|
||||||
|
輸入：EFLOW 送件時要帶 PDF 附件，並確認檔名格式
|
||||||
|
|
||||||
|
輸出：
|
||||||
|
- 層級：Rule + Task
|
||||||
|
- 主專案：P-ONLINE-DOC-AGENT
|
||||||
|
- 子專案：SP-EFLOW / SP-ATTACHMENT-RULES
|
||||||
|
- 任務：定義 EFLOW 附件命名與上傳前檢查規則
|
||||||
|
- 下一步：建立 EFLOW 附件規則草稿 v1
|
||||||
|
|
||||||
|
## Example 2
|
||||||
|
輸入：比較 Stored Procedure 輸出欄位與目標文件欄位差異
|
||||||
|
|
||||||
|
輸出：
|
||||||
|
- 層級：Subproject + Task
|
||||||
|
- 主專案：P-ETL-VISUAL-PLATFORM
|
||||||
|
- 子專案：SP-LLM-DIFF-CHECK
|
||||||
|
- 任務：建立 SP 與目標文件欄位對照表 v1
|
||||||
|
- 下一步：蒐集 SP 欄位清單與目標文件欄位清單
|
||||||
|
|
||||||
|
# Response Style
|
||||||
|
|
||||||
|
- 優先做歸類，再做執行建議
|
||||||
|
- 不把技術類別直接當成主專案
|
||||||
|
- 若工作本質是規則，必須明確指出它不是獨立主專案
|
||||||
@@ -23,6 +23,7 @@
|
|||||||
| `task-capture` | Telegram 快速記錄待辦（自動優先級 + 截止日） | 生活安排 |
|
| `task-capture` | Telegram 快速記錄待辦（自動優先級 + 截止日） | 生活安排 |
|
||||||
| `qmd-brain` | 知識庫搜尋（BM25 + pgvector 向量檢索） | 知識庫 |
|
| `qmd-brain` | 知識庫搜尋（BM25 + pgvector 向量檢索） | 知識庫 |
|
||||||
| `tts-voice` | 文字轉語音（LuxTTS 聲音克隆） | 多媒體 |
|
| `tts-voice` | 文字轉語音（LuxTTS 聲音克隆） | 多媒體 |
|
||||||
|
| `skill-review` | Agent 自動審查 skills 並提交 Gitea PR | DevOps |
|
||||||
|
|
||||||
## 目錄結構
|
## 目錄結構
|
||||||
|
|
||||||
@@ -37,7 +38,8 @@ openclaw-skill/
|
|||||||
│ ├── daily-briefing/ # 每日簡報
|
│ ├── daily-briefing/ # 每日簡報
|
||||||
│ ├── task-capture/ # 快速記錄待辦
|
│ ├── task-capture/ # 快速記錄待辦
|
||||||
│ ├── qmd-brain/ # 知識庫搜尋
|
│ ├── qmd-brain/ # 知識庫搜尋
|
||||||
│ └── tts-voice/ # 文字轉語音
|
│ ├── tts-voice/ # 文字轉語音
|
||||||
|
│ └── skill-review/ # Agent PR 審查工作流
|
||||||
├── chapters/ # 技術手冊分章
|
├── chapters/ # 技術手冊分章
|
||||||
└── openclaw-knowhow-skill/ # OpenClaw 官方文件與範本
|
└── openclaw-knowhow-skill/ # OpenClaw 官方文件與範本
|
||||||
```
|
```
|
||||||
|
|||||||
150
skills/code-interpreter/SKILL.md
Normal file
150
skills/code-interpreter/SKILL.md
Normal file
@@ -0,0 +1,150 @@
|
|||||||
|
---
|
||||||
|
name: code-interpreter
|
||||||
|
description: Local Python code execution for calculations, tabular data inspection, CSV/JSON processing, simple plotting, text transformation, quick experiments, and reproducible analysis inside the OpenClaw workspace. Use when the user wants ChatGPT-style code interpreter behavior locally: run Python, analyze files, compute exact answers, transform data, inspect tables, or generate output files/artifacts. Prefer this for low-risk local analysis; do not use it for untrusted code, secrets handling, privileged actions, or network-dependent tasks.
|
||||||
|
---
|
||||||
|
|
||||||
|
# Code Interpreter
|
||||||
|
|
||||||
|
Run local Python code through the bundled runner.
|
||||||
|
|
||||||
|
## Safety boundary
|
||||||
|
|
||||||
|
This is **local execution**, not a hardened container. Treat it as a convenience tool for trusted, low-risk tasks.
|
||||||
|
|
||||||
|
Always:
|
||||||
|
- Keep work inside the OpenClaw workspace when possible.
|
||||||
|
- Prefer reading/writing files under the current task directory or an explicit artifact directory.
|
||||||
|
- Keep timeouts short by default.
|
||||||
|
- Avoid network access unless the user explicitly asks and the task truly needs it.
|
||||||
|
- Do not execute untrusted code copied from the web or other people.
|
||||||
|
- Do not expose secrets, tokens, SSH keys, browser cookies, or system files to the script.
|
||||||
|
|
||||||
|
Do not use this skill for:
|
||||||
|
- system administration
|
||||||
|
- package installation loops
|
||||||
|
- long-running servers
|
||||||
|
- privileged operations
|
||||||
|
- destructive file changes outside the workspace
|
||||||
|
- executing arbitrary third-party code verbatim
|
||||||
|
|
||||||
|
## Runner
|
||||||
|
|
||||||
|
Run from the OpenClaw workspace:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 {baseDir}/scripts/run_code.py --code 'print(2 + 2)'
|
||||||
|
```
|
||||||
|
|
||||||
|
Or pass a script file:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 {baseDir}/scripts/run_code.py --file path/to/script.py
|
||||||
|
```
|
||||||
|
|
||||||
|
Or pipe code via stdin:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
cat my_script.py | python3 {baseDir}/scripts/run_code.py --stdin
|
||||||
|
```
|
||||||
|
|
||||||
|
## Useful options
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# set timeout seconds (default 20)
|
||||||
|
python3 {baseDir}/scripts/run_code.py --code '...' --timeout 10
|
||||||
|
|
||||||
|
# run from a specific working directory inside workspace
|
||||||
|
python3 {baseDir}/scripts/run_code.py --file script.py --cwd /home/selig/.openclaw/workspace/project
|
||||||
|
|
||||||
|
# keep outputs in a known artifact directory inside workspace
|
||||||
|
python3 {baseDir}/scripts/run_code.py --file script.py --artifact-dir /home/selig/.openclaw/workspace/.tmp/my-analysis
|
||||||
|
|
||||||
|
# save full stdout / stderr
|
||||||
|
python3 {baseDir}/scripts/run_code.py --code '...' --stdout-file out.txt --stderr-file err.txt
|
||||||
|
```
|
||||||
|
|
||||||
|
## Built-in environment
|
||||||
|
|
||||||
|
The runner uses the dedicated interpreter at:
|
||||||
|
|
||||||
|
- `/home/selig/.openclaw/workspace/.venv-code-interpreter/bin/python` (use the venv path directly; do not resolve the symlink to system Python)
|
||||||
|
|
||||||
|
This keeps plotting/data-analysis dependencies stable without touching the system Python.
|
||||||
|
|
||||||
|
The runner exposes these variables to the script:
|
||||||
|
|
||||||
|
- `OPENCLAW_WORKSPACE`
|
||||||
|
- `CODE_INTERPRETER_RUN_DIR`
|
||||||
|
- `CODE_INTERPRETER_ARTIFACT_DIR`
|
||||||
|
|
||||||
|
It also writes a helper file in the run directory:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from ci_helpers import save_text, save_json
|
||||||
|
```
|
||||||
|
|
||||||
|
Use those helpers to save artifacts into `CODE_INTERPRETER_ARTIFACT_DIR`.
|
||||||
|
|
||||||
|
## V4 automatic data analysis
|
||||||
|
|
||||||
|
For automatic profiling/report generation from a local data file, use:
|
||||||
|
|
||||||
|
- `scripts/analyze_data.py`
|
||||||
|
- Reference: `references/v4-usage.md`
|
||||||
|
|
||||||
|
This flow is ideal when the user wants a fast "analyze this CSV/JSON/Excel and give me a report + plots" result.
|
||||||
|
|
||||||
|
## Output
|
||||||
|
|
||||||
|
The runner prints compact JSON:
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"ok": true,
|
||||||
|
"exitCode": 0,
|
||||||
|
"timeout": false,
|
||||||
|
"runDir": "...",
|
||||||
|
"artifactDir": "...",
|
||||||
|
"packageStatus": {"pandas": true, "numpy": true, "matplotlib": false},
|
||||||
|
"artifacts": [{"path": "...", "bytes": 123}],
|
||||||
|
"stdout": "...",
|
||||||
|
"stderr": "..."
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Workflow
|
||||||
|
|
||||||
|
1. Decide whether the task is a good fit for local trusted execution.
|
||||||
|
2. Write the smallest script that solves the problem.
|
||||||
|
3. Use `--artifact-dir` when the user may want generated files preserved.
|
||||||
|
4. Run with a short timeout.
|
||||||
|
5. Inspect `stdout`, `stderr`, and `artifacts`.
|
||||||
|
6. If producing files, mention their exact paths in the reply.
|
||||||
|
|
||||||
|
## Patterns
|
||||||
|
|
||||||
|
### Exact calculation
|
||||||
|
Use a one-liner with `--code`.
|
||||||
|
|
||||||
|
### File analysis
|
||||||
|
Read input files from workspace, then write summaries/derived files back to `artifactDir`.
|
||||||
|
|
||||||
|
### Automatic report bundle
|
||||||
|
When the user wants a quick profiling pass, run `scripts/analyze_data.py` against the file and return the generated `summary.json`, `report.md`, `preview.csv`, and any PNG plots.
|
||||||
|
|
||||||
|
### Table inspection
|
||||||
|
Prefer pandas when available; otherwise fall back to csv/json stdlib.
|
||||||
|
|
||||||
|
### Plotting
|
||||||
|
If `matplotlib` is available, write PNG files to `artifactDir`. Use a forced CJK font strategy for Chinese charts. The bundled default is Google Noto Sans CJK TC under `assets/fonts/` when present, then system fallbacks. Apply the chosen font not only via rcParams but also directly to titles, axis labels, tick labels, and legend text through FontProperties. This avoids tofu/garbled Chinese and suppresses missing-glyph warnings reliably. If plotting is unavailable, continue with tabular/text output.
|
||||||
|
|
||||||
|
### Reusable logic
|
||||||
|
Write a small `.py` file in the current task area, run with `--file`, then keep it if it may be reused.
|
||||||
|
|
||||||
|
## Notes
|
||||||
|
|
||||||
|
- The runner launches `python3 -B` with a minimal environment.
|
||||||
|
- It creates an isolated temp run directory under `workspace/.tmp/code-interpreter-runs/`.
|
||||||
|
- `stdout` / `stderr` are truncated in the JSON preview if very large; save to files when needed.
|
||||||
|
- `MPLBACKEND=Agg` is set so headless plotting works when matplotlib is installed.
|
||||||
|
- If a task needs stronger isolation than this local runner provides, do not force it—use a real sandbox/container approach instead.
|
||||||
BIN
skills/code-interpreter/assets/fonts/NotoSansCJKtc-Regular.otf
Normal file
BIN
skills/code-interpreter/assets/fonts/NotoSansCJKtc-Regular.otf
Normal file
Binary file not shown.
29
skills/code-interpreter/references/v4-usage.md
Normal file
29
skills/code-interpreter/references/v4-usage.md
Normal file
@@ -0,0 +1,29 @@
|
|||||||
|
# V4 Usage
|
||||||
|
|
||||||
|
## Purpose
|
||||||
|
|
||||||
|
Generate an automatic data analysis bundle from a local data file.
|
||||||
|
|
||||||
|
## Command
|
||||||
|
|
||||||
|
```bash
|
||||||
|
/home/selig/.openclaw/workspace/.venv-code-interpreter/bin/python \
|
||||||
|
/home/selig/.openclaw/workspace/skills/code-interpreter/scripts/analyze_data.py \
|
||||||
|
/path/to/input.csv \
|
||||||
|
--artifact-dir /home/selig/.openclaw/workspace/.tmp/my-analysis
|
||||||
|
```
|
||||||
|
|
||||||
|
## Outputs
|
||||||
|
|
||||||
|
- `summary.json` — machine-readable profile
|
||||||
|
- `report.md` — human-readable summary
|
||||||
|
- `preview.csv` — first 50 rows after parsing
|
||||||
|
- `*.png` — generated plots when matplotlib is available
|
||||||
|
|
||||||
|
## Supported inputs
|
||||||
|
|
||||||
|
- `.csv`
|
||||||
|
- `.tsv`
|
||||||
|
- `.json`
|
||||||
|
- `.xlsx`
|
||||||
|
- `.xls`
|
||||||
Binary file not shown.
Binary file not shown.
285
skills/code-interpreter/scripts/analyze_data.py
Normal file
285
skills/code-interpreter/scripts/analyze_data.py
Normal file
@@ -0,0 +1,285 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import math
|
||||||
|
import os
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
try:
|
||||||
|
import pandas as pd
|
||||||
|
except ImportError:
|
||||||
|
raise SystemExit(
|
||||||
|
'pandas is required. Run with the code-interpreter venv:\n'
|
||||||
|
' ~/.openclaw/workspace/.venv-code-interpreter/bin/python analyze_data.py ...'
|
||||||
|
)
|
||||||
|
|
||||||
|
try:
|
||||||
|
import matplotlib
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
HAS_MPL = True
|
||||||
|
except Exception:
|
||||||
|
HAS_MPL = False
|
||||||
|
|
||||||
|
ZH_FONT_CANDIDATES = [
|
||||||
|
'/home/selig/.openclaw/workspace/skills/code-interpreter/assets/fonts/NotoSansCJKtc-Regular.otf',
|
||||||
|
'/usr/share/fonts/truetype/droid/DroidSansFallbackFull.ttf',
|
||||||
|
]
|
||||||
|
|
||||||
|
|
||||||
|
def configure_matplotlib_fonts() -> tuple[str | None, object | None]:
|
||||||
|
if not HAS_MPL:
|
||||||
|
return None, None
|
||||||
|
chosen = None
|
||||||
|
chosen_prop = None
|
||||||
|
for path in ZH_FONT_CANDIDATES:
|
||||||
|
if Path(path).exists():
|
||||||
|
try:
|
||||||
|
from matplotlib import font_manager
|
||||||
|
font_manager.fontManager.addfont(path)
|
||||||
|
font_prop = font_manager.FontProperties(fname=path)
|
||||||
|
font_name = font_prop.get_name()
|
||||||
|
matplotlib.rcParams['font.family'] = [font_name]
|
||||||
|
matplotlib.rcParams['axes.unicode_minus'] = False
|
||||||
|
chosen = font_name
|
||||||
|
chosen_prop = font_prop
|
||||||
|
break
|
||||||
|
except Exception:
|
||||||
|
continue
|
||||||
|
return chosen, chosen_prop
|
||||||
|
|
||||||
|
|
||||||
|
def apply_font(ax, font_prop) -> None:
|
||||||
|
if not font_prop:
|
||||||
|
return
|
||||||
|
title = ax.title
|
||||||
|
if title:
|
||||||
|
title.set_fontproperties(font_prop)
|
||||||
|
ax.xaxis.label.set_fontproperties(font_prop)
|
||||||
|
ax.yaxis.label.set_fontproperties(font_prop)
|
||||||
|
for label in ax.get_xticklabels():
|
||||||
|
label.set_fontproperties(font_prop)
|
||||||
|
for label in ax.get_yticklabels():
|
||||||
|
label.set_fontproperties(font_prop)
|
||||||
|
legend = ax.get_legend()
|
||||||
|
if legend:
|
||||||
|
for text in legend.get_texts():
|
||||||
|
text.set_fontproperties(font_prop)
|
||||||
|
legend.get_title().set_fontproperties(font_prop)
|
||||||
|
|
||||||
|
|
||||||
|
def detect_format(path: Path) -> str:
|
||||||
|
ext = path.suffix.lower()
|
||||||
|
if ext in {'.csv', '.tsv', '.txt'}:
|
||||||
|
return 'delimited'
|
||||||
|
if ext == '.json':
|
||||||
|
return 'json'
|
||||||
|
if ext in {'.xlsx', '.xls'}:
|
||||||
|
return 'excel'
|
||||||
|
raise SystemExit(f'Unsupported file type: {ext}')
|
||||||
|
|
||||||
|
|
||||||
|
def load_df(path: Path) -> pd.DataFrame:
|
||||||
|
fmt = detect_format(path)
|
||||||
|
if fmt == 'delimited':
|
||||||
|
sep = '\t' if path.suffix.lower() == '.tsv' else ','
|
||||||
|
return pd.read_csv(path, sep=sep)
|
||||||
|
if fmt == 'json':
|
||||||
|
try:
|
||||||
|
return pd.read_json(path)
|
||||||
|
except ValueError:
|
||||||
|
return pd.DataFrame(json.loads(path.read_text(encoding='utf-8')))
|
||||||
|
if fmt == 'excel':
|
||||||
|
return pd.read_excel(path)
|
||||||
|
raise SystemExit('Unsupported format')
|
||||||
|
|
||||||
|
|
||||||
|
def safe_name(s: str) -> str:
|
||||||
|
keep = []
|
||||||
|
for ch in s:
|
||||||
|
if ch.isalnum() or ch in ('-', '_'):
|
||||||
|
keep.append(ch)
|
||||||
|
elif ch in (' ', '/'):
|
||||||
|
keep.append('_')
|
||||||
|
out = ''.join(keep).strip('_')
|
||||||
|
return out[:80] or 'column'
|
||||||
|
|
||||||
|
|
||||||
|
def series_stats(s: pd.Series) -> dict:
|
||||||
|
non_null = s.dropna()
|
||||||
|
result = {
|
||||||
|
'dtype': str(s.dtype),
|
||||||
|
'nonNull': int(non_null.shape[0]),
|
||||||
|
'nulls': int(s.isna().sum()),
|
||||||
|
'unique': int(non_null.nunique()) if len(non_null) else 0,
|
||||||
|
}
|
||||||
|
if pd.api.types.is_numeric_dtype(s):
|
||||||
|
result.update({
|
||||||
|
'min': None if non_null.empty else float(non_null.min()),
|
||||||
|
'max': None if non_null.empty else float(non_null.max()),
|
||||||
|
'mean': None if non_null.empty else float(non_null.mean()),
|
||||||
|
'sum': None if non_null.empty else float(non_null.sum()),
|
||||||
|
})
|
||||||
|
else:
|
||||||
|
top = non_null.astype(str).value_counts().head(5)
|
||||||
|
result['topValues'] = [{
|
||||||
|
'value': str(idx),
|
||||||
|
'count': int(val),
|
||||||
|
} for idx, val in top.items()]
|
||||||
|
return result
|
||||||
|
|
||||||
|
|
||||||
|
def maybe_parse_dates(df: pd.DataFrame) -> tuple[pd.DataFrame, list[str]]:
|
||||||
|
parsed = []
|
||||||
|
out = df.copy()
|
||||||
|
for col in out.columns:
|
||||||
|
if out[col].dtype == 'object':
|
||||||
|
sample = out[col].dropna().astype(str).head(20)
|
||||||
|
if sample.empty:
|
||||||
|
continue
|
||||||
|
parsed_col = pd.to_datetime(out[col], errors='coerce')
|
||||||
|
success_ratio = float(parsed_col.notna().mean()) if len(out[col]) else 0.0
|
||||||
|
if success_ratio >= 0.6:
|
||||||
|
out[col] = parsed_col
|
||||||
|
parsed.append(str(col))
|
||||||
|
return out, parsed
|
||||||
|
|
||||||
|
|
||||||
|
def write_report(df: pd.DataFrame, summary: dict, out_dir: Path) -> Path:
|
||||||
|
lines = []
|
||||||
|
lines.append('# Data Analysis Report')
|
||||||
|
lines.append('')
|
||||||
|
lines.append(f"- Source: `{summary['source']}`")
|
||||||
|
lines.append(f"- Rows: **{summary['rows']}**")
|
||||||
|
lines.append(f"- Columns: **{summary['columns']}**")
|
||||||
|
lines.append(f"- Generated plots: **{len(summary['plots'])}**")
|
||||||
|
if summary['parsedDateColumns']:
|
||||||
|
lines.append(f"- Parsed date columns: {', '.join(summary['parsedDateColumns'])}")
|
||||||
|
lines.append('')
|
||||||
|
lines.append('## Columns')
|
||||||
|
lines.append('')
|
||||||
|
for name, meta in summary['columnProfiles'].items():
|
||||||
|
lines.append(f"### {name}")
|
||||||
|
lines.append(f"- dtype: `{meta['dtype']}`")
|
||||||
|
lines.append(f"- non-null: {meta['nonNull']}")
|
||||||
|
lines.append(f"- nulls: {meta['nulls']}")
|
||||||
|
lines.append(f"- unique: {meta['unique']}")
|
||||||
|
if 'mean' in meta:
|
||||||
|
lines.append(f"- min / max: {meta['min']} / {meta['max']}")
|
||||||
|
lines.append(f"- mean / sum: {meta['mean']} / {meta['sum']}")
|
||||||
|
elif meta.get('topValues'):
|
||||||
|
preview = ', '.join([f"{x['value']} ({x['count']})" for x in meta['topValues'][:5]])
|
||||||
|
lines.append(f"- top values: {preview}")
|
||||||
|
lines.append('')
|
||||||
|
report = out_dir / 'report.md'
|
||||||
|
report.write_text('\n'.join(lines).strip() + '\n', encoding='utf-8')
|
||||||
|
return report
|
||||||
|
|
||||||
|
|
||||||
|
def generate_plots(df: pd.DataFrame, out_dir: Path, font_prop=None) -> list[str]:
|
||||||
|
if not HAS_MPL:
|
||||||
|
return []
|
||||||
|
plots = []
|
||||||
|
numeric_cols = [c for c in df.columns if pd.api.types.is_numeric_dtype(df[c])]
|
||||||
|
date_cols = [c for c in df.columns if pd.api.types.is_datetime64_any_dtype(df[c])]
|
||||||
|
cat_cols = [c for c in df.columns if not pd.api.types.is_numeric_dtype(df[c]) and not pd.api.types.is_datetime64_any_dtype(df[c])]
|
||||||
|
|
||||||
|
if numeric_cols:
|
||||||
|
col = numeric_cols[0]
|
||||||
|
plt.figure(figsize=(7, 4))
|
||||||
|
bins = min(20, max(5, int(math.sqrt(max(1, df[col].dropna().shape[0])))))
|
||||||
|
df[col].dropna().hist(bins=bins)
|
||||||
|
plt.title(f'Histogram of {col}', fontproperties=font_prop)
|
||||||
|
plt.xlabel(str(col), fontproperties=font_prop)
|
||||||
|
plt.ylabel('Count', fontproperties=font_prop)
|
||||||
|
apply_font(plt.gca(), font_prop)
|
||||||
|
path = out_dir / f'hist_{safe_name(str(col))}.png'
|
||||||
|
plt.tight_layout()
|
||||||
|
plt.savefig(path, dpi=160)
|
||||||
|
plt.close()
|
||||||
|
plots.append(str(path))
|
||||||
|
|
||||||
|
if cat_cols and numeric_cols:
|
||||||
|
cat, num = cat_cols[0], numeric_cols[0]
|
||||||
|
grp = df.groupby(cat, dropna=False)[num].sum().sort_values(ascending=False).head(12)
|
||||||
|
if not grp.empty:
|
||||||
|
plt.figure(figsize=(8, 4.5))
|
||||||
|
grp.plot(kind='bar')
|
||||||
|
plt.title(f'{num} by {cat}', fontproperties=font_prop)
|
||||||
|
plt.xlabel(str(cat), fontproperties=font_prop)
|
||||||
|
plt.ylabel(f'Sum of {num}', fontproperties=font_prop)
|
||||||
|
apply_font(plt.gca(), font_prop)
|
||||||
|
plt.tight_layout()
|
||||||
|
path = out_dir / f'bar_{safe_name(str(num))}_by_{safe_name(str(cat))}.png'
|
||||||
|
plt.savefig(path, dpi=160)
|
||||||
|
plt.close()
|
||||||
|
plots.append(str(path))
|
||||||
|
|
||||||
|
if date_cols and numeric_cols:
|
||||||
|
date_col, num = date_cols[0], numeric_cols[0]
|
||||||
|
grp = df[[date_col, num]].dropna().sort_values(date_col)
|
||||||
|
if not grp.empty:
|
||||||
|
plt.figure(figsize=(8, 4.5))
|
||||||
|
plt.plot(grp[date_col], grp[num], marker='o')
|
||||||
|
plt.title(f'{num} over time', fontproperties=font_prop)
|
||||||
|
plt.xlabel(str(date_col), fontproperties=font_prop)
|
||||||
|
plt.ylabel(str(num), fontproperties=font_prop)
|
||||||
|
apply_font(plt.gca(), font_prop)
|
||||||
|
plt.tight_layout()
|
||||||
|
path = out_dir / f'line_{safe_name(str(num))}_over_time.png'
|
||||||
|
plt.savefig(path, dpi=160)
|
||||||
|
plt.close()
|
||||||
|
plots.append(str(path))
|
||||||
|
|
||||||
|
return plots
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> int:
|
||||||
|
parser = argparse.ArgumentParser(description='Automatic data analysis report generator')
|
||||||
|
parser.add_argument('input', help='Input data file (csv/json/xlsx)')
|
||||||
|
parser.add_argument('--artifact-dir', required=True, help='Output artifact directory')
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
input_path = Path(args.input).expanduser().resolve()
|
||||||
|
artifact_dir = Path(args.artifact_dir).expanduser().resolve()
|
||||||
|
artifact_dir.mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
df = load_df(input_path)
|
||||||
|
original_columns = [str(c) for c in df.columns]
|
||||||
|
df, parsed_dates = maybe_parse_dates(df)
|
||||||
|
chosen_font, chosen_font_prop = configure_matplotlib_fonts()
|
||||||
|
|
||||||
|
preview_path = artifact_dir / 'preview.csv'
|
||||||
|
df.head(50).to_csv(preview_path, index=False)
|
||||||
|
|
||||||
|
summary = {
|
||||||
|
'source': str(input_path),
|
||||||
|
'rows': int(df.shape[0]),
|
||||||
|
'columns': int(df.shape[1]),
|
||||||
|
'columnNames': original_columns,
|
||||||
|
'parsedDateColumns': parsed_dates,
|
||||||
|
'columnProfiles': {str(c): series_stats(df[c]) for c in df.columns},
|
||||||
|
'plots': [],
|
||||||
|
'plotFont': chosen_font,
|
||||||
|
}
|
||||||
|
|
||||||
|
summary['plots'] = generate_plots(df, artifact_dir, chosen_font_prop)
|
||||||
|
|
||||||
|
summary_path = artifact_dir / 'summary.json'
|
||||||
|
summary_path.write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding='utf-8')
|
||||||
|
report_path = write_report(df, summary, artifact_dir)
|
||||||
|
|
||||||
|
result = {
|
||||||
|
'ok': True,
|
||||||
|
'input': str(input_path),
|
||||||
|
'artifactDir': str(artifact_dir),
|
||||||
|
'summary': str(summary_path),
|
||||||
|
'report': str(report_path),
|
||||||
|
'preview': str(preview_path),
|
||||||
|
'plots': summary['plots'],
|
||||||
|
}
|
||||||
|
print(json.dumps(result, ensure_ascii=False, indent=2))
|
||||||
|
return 0
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
raise SystemExit(main())
|
||||||
241
skills/code-interpreter/scripts/run_code.py
Normal file
241
skills/code-interpreter/scripts/run_code.py
Normal file
@@ -0,0 +1,241 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
import argparse
|
||||||
|
import importlib.util
|
||||||
|
import json
|
||||||
|
import os
|
||||||
|
import pathlib
|
||||||
|
import shutil
|
||||||
|
import subprocess
|
||||||
|
import sys
|
||||||
|
import tempfile
|
||||||
|
import time
|
||||||
|
from typing import Optional
|
||||||
|
|
||||||
|
WORKSPACE = pathlib.Path('/home/selig/.openclaw/workspace').resolve()
|
||||||
|
RUNS_DIR = WORKSPACE / '.tmp' / 'code-interpreter-runs'
|
||||||
|
MAX_PREVIEW = 12000
|
||||||
|
ARTIFACT_SCAN_LIMIT = 100
|
||||||
|
PACKAGE_PROBES = ['pandas', 'numpy', 'matplotlib']
|
||||||
|
PYTHON_BIN = str(WORKSPACE / '.venv-code-interpreter' / 'bin' / 'python')
|
||||||
|
|
||||||
|
|
||||||
|
def current_python_paths(run_dir_path: pathlib.Path) -> str:
|
||||||
|
"""Build PYTHONPATH: run_dir (for ci_helpers) only.
|
||||||
|
Venv site-packages are already on sys.path when using PYTHON_BIN."""
|
||||||
|
return str(run_dir_path)
|
||||||
|
|
||||||
|
|
||||||
|
def read_code(args: argparse.Namespace) -> str:
|
||||||
|
sources = [bool(args.code), bool(args.file), bool(args.stdin)]
|
||||||
|
if sum(sources) != 1:
|
||||||
|
raise SystemExit('Provide exactly one of --code, --file, or --stdin')
|
||||||
|
if args.code:
|
||||||
|
return args.code
|
||||||
|
if args.file:
|
||||||
|
return pathlib.Path(args.file).read_text(encoding='utf-8')
|
||||||
|
return sys.stdin.read()
|
||||||
|
|
||||||
|
|
||||||
|
def ensure_within_workspace(path_str: Optional[str], must_exist: bool = True) -> pathlib.Path:
|
||||||
|
if not path_str:
|
||||||
|
return WORKSPACE
|
||||||
|
p = pathlib.Path(path_str).expanduser().resolve()
|
||||||
|
if p != WORKSPACE and WORKSPACE not in p.parents:
|
||||||
|
raise SystemExit(f'Path must stay inside workspace: {WORKSPACE}')
|
||||||
|
if must_exist and (not p.exists() or not p.is_dir()):
|
||||||
|
raise SystemExit(f'Path not found or not a directory: {p}')
|
||||||
|
return p
|
||||||
|
|
||||||
|
|
||||||
|
def ensure_output_path(path_str: Optional[str]) -> Optional[pathlib.Path]:
|
||||||
|
if not path_str:
|
||||||
|
return None
|
||||||
|
p = pathlib.Path(path_str).expanduser().resolve()
|
||||||
|
p.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
return p
|
||||||
|
|
||||||
|
|
||||||
|
def write_text(path_str: Optional[str], text: str) -> None:
|
||||||
|
p = ensure_output_path(path_str)
|
||||||
|
if not p:
|
||||||
|
return
|
||||||
|
p.write_text(text, encoding='utf-8')
|
||||||
|
|
||||||
|
|
||||||
|
def truncate(text: str) -> str:
|
||||||
|
if len(text) <= MAX_PREVIEW:
|
||||||
|
return text
|
||||||
|
extra = len(text) - MAX_PREVIEW
|
||||||
|
return text[:MAX_PREVIEW] + f'\n...[truncated {extra} chars]'
|
||||||
|
|
||||||
|
|
||||||
|
def package_status() -> dict:
|
||||||
|
out: dict[str, bool] = {}
|
||||||
|
for name in PACKAGE_PROBES:
|
||||||
|
proc = subprocess.run(
|
||||||
|
[PYTHON_BIN, '-c', f"import importlib.util; print('1' if importlib.util.find_spec('{name}') else '0')"],
|
||||||
|
capture_output=True,
|
||||||
|
text=True,
|
||||||
|
encoding='utf-8',
|
||||||
|
errors='replace',
|
||||||
|
)
|
||||||
|
out[name] = proc.stdout.strip() == '1'
|
||||||
|
return out
|
||||||
|
|
||||||
|
|
||||||
|
def rel_to(path: pathlib.Path, base: pathlib.Path) -> str:
|
||||||
|
try:
|
||||||
|
return str(path.relative_to(base))
|
||||||
|
except Exception:
|
||||||
|
return str(path)
|
||||||
|
|
||||||
|
|
||||||
|
def scan_artifacts(base_dir: pathlib.Path, root_label: str) -> list[dict]:
|
||||||
|
if not base_dir.exists():
|
||||||
|
return []
|
||||||
|
items: list[dict] = []
|
||||||
|
for p in sorted(base_dir.rglob('*')):
|
||||||
|
if len(items) >= ARTIFACT_SCAN_LIMIT:
|
||||||
|
break
|
||||||
|
if p.is_file():
|
||||||
|
try:
|
||||||
|
size = p.stat().st_size
|
||||||
|
except Exception:
|
||||||
|
size = None
|
||||||
|
items.append({
|
||||||
|
'root': root_label,
|
||||||
|
'path': str(p),
|
||||||
|
'relative': rel_to(p, base_dir),
|
||||||
|
'bytes': size,
|
||||||
|
})
|
||||||
|
return items
|
||||||
|
|
||||||
|
|
||||||
|
def write_helper(run_dir_path: pathlib.Path, artifact_dir: pathlib.Path) -> None:
|
||||||
|
helper = run_dir_path / 'ci_helpers.py'
|
||||||
|
helper.write_text(
|
||||||
|
"""
|
||||||
|
from pathlib import Path
|
||||||
|
import json
|
||||||
|
import os
|
||||||
|
|
||||||
|
WORKSPACE = Path(os.environ['OPENCLAW_WORKSPACE'])
|
||||||
|
RUN_DIR = Path(os.environ['CODE_INTERPRETER_RUN_DIR'])
|
||||||
|
ARTIFACT_DIR = Path(os.environ['CODE_INTERPRETER_ARTIFACT_DIR'])
|
||||||
|
|
||||||
|
|
||||||
|
def save_text(name: str, text: str) -> str:
|
||||||
|
path = ARTIFACT_DIR / name
|
||||||
|
path.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
path.write_text(text, encoding='utf-8')
|
||||||
|
return str(path)
|
||||||
|
|
||||||
|
|
||||||
|
def save_json(name: str, data) -> str:
|
||||||
|
path = ARTIFACT_DIR / name
|
||||||
|
path.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
path.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding='utf-8')
|
||||||
|
return str(path)
|
||||||
|
""".lstrip(),
|
||||||
|
encoding='utf-8',
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> int:
|
||||||
|
parser = argparse.ArgumentParser(description='Local Python runner for OpenClaw code-interpreter skill')
|
||||||
|
parser.add_argument('--code', help='Python code to execute')
|
||||||
|
parser.add_argument('--file', help='Path to a Python file to execute')
|
||||||
|
parser.add_argument('--stdin', action='store_true', help='Read Python code from stdin')
|
||||||
|
parser.add_argument('--cwd', help='Working directory inside workspace')
|
||||||
|
parser.add_argument('--artifact-dir', help='Artifact directory inside workspace to keep outputs')
|
||||||
|
parser.add_argument('--timeout', type=int, default=20, help='Timeout seconds (default: 20)')
|
||||||
|
parser.add_argument('--stdout-file', help='Optional file path to save full stdout')
|
||||||
|
parser.add_argument('--stderr-file', help='Optional file path to save full stderr')
|
||||||
|
parser.add_argument('--keep-run-dir', action='store_true', help='Keep generated temp run directory even on success')
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
code = read_code(args)
|
||||||
|
cwd = ensure_within_workspace(args.cwd)
|
||||||
|
RUNS_DIR.mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
run_dir_path = pathlib.Path(tempfile.mkdtemp(prefix='run-', dir=str(RUNS_DIR))).resolve()
|
||||||
|
artifact_dir = ensure_within_workspace(args.artifact_dir, must_exist=False) if args.artifact_dir else (run_dir_path / 'artifacts')
|
||||||
|
artifact_dir.mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
script_path = run_dir_path / 'main.py'
|
||||||
|
script_path.write_text(code, encoding='utf-8')
|
||||||
|
write_helper(run_dir_path, artifact_dir)
|
||||||
|
|
||||||
|
env = {
|
||||||
|
'PATH': os.environ.get('PATH', '/usr/bin:/bin'),
|
||||||
|
'HOME': str(run_dir_path),
|
||||||
|
'PYTHONPATH': current_python_paths(run_dir_path),
|
||||||
|
'PYTHONIOENCODING': 'utf-8',
|
||||||
|
'PYTHONUNBUFFERED': '1',
|
||||||
|
'OPENCLAW_WORKSPACE': str(WORKSPACE),
|
||||||
|
'CODE_INTERPRETER_RUN_DIR': str(run_dir_path),
|
||||||
|
'CODE_INTERPRETER_ARTIFACT_DIR': str(artifact_dir),
|
||||||
|
'MPLBACKEND': 'Agg',
|
||||||
|
}
|
||||||
|
|
||||||
|
started = time.time()
|
||||||
|
timed_out = False
|
||||||
|
exit_code = None
|
||||||
|
stdout = ''
|
||||||
|
stderr = ''
|
||||||
|
|
||||||
|
try:
|
||||||
|
proc = subprocess.run(
|
||||||
|
[PYTHON_BIN, '-B', str(script_path)],
|
||||||
|
cwd=str(cwd),
|
||||||
|
env=env,
|
||||||
|
capture_output=True,
|
||||||
|
text=True,
|
||||||
|
encoding='utf-8',
|
||||||
|
errors='replace',
|
||||||
|
timeout=max(1, args.timeout),
|
||||||
|
)
|
||||||
|
exit_code = proc.returncode
|
||||||
|
stdout = proc.stdout
|
||||||
|
stderr = proc.stderr
|
||||||
|
except subprocess.TimeoutExpired as exc:
|
||||||
|
timed_out = True
|
||||||
|
exit_code = 124
|
||||||
|
raw_out = exc.stdout or ''
|
||||||
|
raw_err = exc.stderr or ''
|
||||||
|
stdout = raw_out if isinstance(raw_out, str) else raw_out.decode('utf-8', errors='replace')
|
||||||
|
stderr = (raw_err if isinstance(raw_err, str) else raw_err.decode('utf-8', errors='replace')) + f'\nExecution timed out after {args.timeout}s.'
|
||||||
|
|
||||||
|
duration = round(time.time() - started, 3)
|
||||||
|
|
||||||
|
write_text(args.stdout_file, stdout)
|
||||||
|
write_text(args.stderr_file, stderr)
|
||||||
|
|
||||||
|
artifacts = scan_artifacts(artifact_dir, 'artifactDir')
|
||||||
|
if artifact_dir != run_dir_path:
|
||||||
|
artifacts.extend(scan_artifacts(run_dir_path / 'artifacts', 'runArtifacts'))
|
||||||
|
|
||||||
|
result = {
|
||||||
|
'ok': (exit_code == 0 and not timed_out),
|
||||||
|
'exitCode': exit_code,
|
||||||
|
'timeout': timed_out,
|
||||||
|
'durationSec': duration,
|
||||||
|
'cwd': str(cwd),
|
||||||
|
'runDir': str(run_dir_path),
|
||||||
|
'artifactDir': str(artifact_dir),
|
||||||
|
'packageStatus': package_status(),
|
||||||
|
'artifacts': artifacts,
|
||||||
|
'stdout': truncate(stdout),
|
||||||
|
'stderr': truncate(stderr),
|
||||||
|
}
|
||||||
|
|
||||||
|
print(json.dumps(result, ensure_ascii=False, indent=2))
|
||||||
|
|
||||||
|
if not args.keep_run_dir and result['ok'] and artifact_dir != run_dir_path:
|
||||||
|
shutil.rmtree(run_dir_path, ignore_errors=True)
|
||||||
|
|
||||||
|
return 0 if result['ok'] else 1
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
raise SystemExit(main())
|
||||||
@@ -12,6 +12,56 @@ interface DispatchInput {
|
|||||||
retries?: number;
|
retries?: number;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
const ALLOWED_TARGETS = new Set<DispatchInput['target']>(['vps-a', 'vps-b']);
|
||||||
|
|
||||||
|
function clampInt(value: unknown, min: number, max: number, fallback: number): number {
|
||||||
|
const n = Number(value);
|
||||||
|
if (!Number.isFinite(n)) return fallback;
|
||||||
|
return Math.min(max, Math.max(min, Math.floor(n)));
|
||||||
|
}
|
||||||
|
|
||||||
|
function sanitizeTaskId(taskId: unknown): string {
|
||||||
|
if (taskId == null) return '';
|
||||||
|
return String(taskId).replace(/[\r\n]/g, '').slice(0, 128);
|
||||||
|
}
|
||||||
|
|
||||||
|
function validateInput(raw: any): DispatchInput {
|
||||||
|
const input = raw as Partial<DispatchInput>;
|
||||||
|
|
||||||
|
if (!input || typeof input !== 'object') {
|
||||||
|
throw new Error('dispatch-webhook 輸入格式錯誤：必須提供 input 物件');
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!input.target || !ALLOWED_TARGETS.has(input.target as DispatchInput['target'])) {
|
||||||
|
throw new Error('dispatch-webhook 參數錯誤：target 必須是 vps-a 或 vps-b');
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!input.webhookUrl || typeof input.webhookUrl !== 'string') {
|
||||||
|
throw new Error(`${input.target.toUpperCase()} Webhook URL 未設定。請在環境變數設定 VPS_A_WEBHOOK_URL 或 VPS_B_WEBHOOK_URL`);
|
||||||
|
}
|
||||||
|
|
||||||
|
let parsedUrl: URL;
|
||||||
|
try {
|
||||||
|
parsedUrl = new URL(input.webhookUrl);
|
||||||
|
} catch {
|
||||||
|
throw new Error('Webhook URL 格式錯誤，請提供有效的 http/https URL');
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!['http:', 'https:'].includes(parsedUrl.protocol)) {
|
||||||
|
throw new Error('Webhook URL 協定不支援，僅允許 http 或 https');
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!input.webhookToken || typeof input.webhookToken !== 'string') {
|
||||||
|
throw new Error(`${input.target.toUpperCase()} Webhook Token 未設定`);
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!input.payload || typeof input.payload !== 'object' || Array.isArray(input.payload)) {
|
||||||
|
throw new Error('dispatch-webhook 參數錯誤：payload 必須是 JSON 物件');
|
||||||
|
}
|
||||||
|
|
||||||
|
return input as DispatchInput;
|
||||||
|
}
|
||||||
|
|
||||||
async function fetchWithTimeout(url: string, options: RequestInit, timeoutMs: number): Promise<Response> {
|
async function fetchWithTimeout(url: string, options: RequestInit, timeoutMs: number): Promise<Response> {
|
||||||
const controller = new AbortController();
|
const controller = new AbortController();
|
||||||
const timer = setTimeout(() => controller.abort(), timeoutMs);
|
const timer = setTimeout(() => controller.abort(), timeoutMs);
|
||||||
@@ -23,17 +73,11 @@ async function fetchWithTimeout(url: string, options: RequestInit, timeoutMs: nu
|
|||||||
}
|
}
|
||||||
|
|
||||||
export async function handler(ctx: any) {
|
export async function handler(ctx: any) {
|
||||||
const input: DispatchInput = ctx.input || ctx.params;
|
const input = validateInput(ctx.input || ctx.params);
|
||||||
|
|
||||||
if (!input.webhookUrl) {
|
const timeoutMs = clampInt(input.timeoutMs, 1000, 120000, 30000);
|
||||||
throw new Error(`${input.target.toUpperCase()} Webhook URL 未設定。請在環境變數設定 VPS_A_WEBHOOK_URL 或 VPS_B_WEBHOOK_URL`);
|
const maxRetries = clampInt(input.retries, 1, 5, 3);
|
||||||
}
|
const taskIdHeader = sanitizeTaskId(input.payload.task_id);
|
||||||
if (!input.webhookToken) {
|
|
||||||
throw new Error(`${input.target.toUpperCase()} Webhook Token 未設定`);
|
|
||||||
}
|
|
||||||
|
|
||||||
const timeoutMs = input.timeoutMs ?? 30000;
|
|
||||||
const maxRetries = input.retries ?? 3;
|
|
||||||
let lastError: Error | null = null;
|
let lastError: Error | null = null;
|
||||||
|
|
||||||
for (let attempt = 1; attempt <= maxRetries; attempt++) {
|
for (let attempt = 1; attempt <= maxRetries; attempt++) {
|
||||||
@@ -46,7 +90,7 @@ export async function handler(ctx: any) {
|
|||||||
'Content-Type': 'application/json',
|
'Content-Type': 'application/json',
|
||||||
'Authorization': `Bearer ${input.webhookToken}`,
|
'Authorization': `Bearer ${input.webhookToken}`,
|
||||||
'X-OpenClaw-Version': '1.0',
|
'X-OpenClaw-Version': '1.0',
|
||||||
'X-OpenClaw-Task-Id': String(input.payload.task_id || ''),
|
'X-OpenClaw-Task-Id': taskIdHeader,
|
||||||
},
|
},
|
||||||
body: JSON.stringify(input.payload),
|
body: JSON.stringify(input.payload),
|
||||||
},
|
},
|
||||||
@@ -72,8 +116,8 @@ export async function handler(ctx: any) {
|
|||||||
};
|
};
|
||||||
|
|
||||||
} catch (err: any) {
|
} catch (err: any) {
|
||||||
lastError = err;
|
lastError = err instanceof Error ? err : new Error(String(err));
|
||||||
if (err.message?.includes('401') || err.message?.includes('Token')) {
|
if (lastError.message.includes('401') || lastError.message.includes('Token')) {
|
||||||
break; // 認證錯誤不重試
|
break; // 認證錯誤不重試
|
||||||
}
|
}
|
||||||
if (attempt < maxRetries) {
|
if (attempt < maxRetries) {
|
||||||
|
|||||||
1
skills/kokoro-tts
Symbolic link
1
skills/kokoro-tts
Symbolic link
@@ -0,0 +1 @@
|
|||||||
|
/home/selig/.openclaw/workspace/skills/kokoro-tts
|
||||||
1
skills/remotion-best-practices
Symbolic link
1
skills/remotion-best-practices
Symbolic link
@@ -0,0 +1 @@
|
|||||||
|
/home/selig/.agents/skills/remotion-best-practices
|
||||||
125
skills/research-to-paper-slides/SKILL.md
Normal file
125
skills/research-to-paper-slides/SKILL.md
Normal file
@@ -0,0 +1,125 @@
|
|||||||
|
---
|
||||||
|
name: research-to-paper-slides
|
||||||
|
description: Turn local analysis outputs into publication-style drafts and presentation materials. Use when the user already has research/data-analysis artifacts such as summary.json, report.md, preview.csv, plots, or code-interpreter output and wants a complete first-pass paper draft, slide outline, speaker notes, or HTML deck. Especially useful after using the code-interpreter skill on small-to-medium datasets and the next step is to package findings into a paper, report, pitch deck, class slides, or meeting presentation.
|
||||||
|
---
|
||||||
|
|
||||||
|
# research-to-paper-slides
|
||||||
|
|
||||||
|
Generate a complete first-pass writing bundle from analysis artifacts.
|
||||||
|
|
||||||
|
## Inputs
|
||||||
|
|
||||||
|
Best input bundle:
|
||||||
|
- `summary.json`
|
||||||
|
- `report.md`
|
||||||
|
- one or more plot PNG files
|
||||||
|
|
||||||
|
Optional:
|
||||||
|
- `preview.csv`
|
||||||
|
- raw CSV/JSON/XLSX path for source naming only
|
||||||
|
- extra notes from the user (audience, tone, purpose)
|
||||||
|
|
||||||
|
## Levels
|
||||||
|
|
||||||
|
Choose how far the workflow should go:
|
||||||
|
|
||||||
|
- `--level v2` — **基礎交付版**
|
||||||
|
- 輸出：`paper.md`、`slides.md`、`speaker-notes.md`、`deck.html`
|
||||||
|
- 適合：快速草稿、先出第一版內容
|
||||||
|
- 不包含：`insights.md`、逐圖解讀頁、正式 deck 視覺強化
|
||||||
|
|
||||||
|
- `--level v3` — **洞察強化版**
|
||||||
|
- 包含 `v2` 全部內容
|
||||||
|
- 另外增加：`insights.md`、每張圖各一頁解讀、speaker notes 逐圖講稿
|
||||||
|
- 適合：內部討論、研究整理、需要把圖表講清楚
|
||||||
|
|
||||||
|
- `--level v4` — **正式交付版**
|
||||||
|
- 包含 `v3` 全部內容
|
||||||
|
- 另外增加：更正式的 deck 視覺版面、PDF-ready 工作流
|
||||||
|
- 適合：正式簡報、提案、對外展示
|
||||||
|
|
||||||
|
## Modes
|
||||||
|
|
||||||
|
- `academic` — 論文/研究報告/研討會簡報
|
||||||
|
- `business` — 內部決策/管理匯報/策略說明
|
||||||
|
- `pitch` — 提案/募資/對外說服型簡報
|
||||||
|
|
||||||
|
## Outputs
|
||||||
|
|
||||||
|
Depending on `--level`, the generator creates:
|
||||||
|
- `paper.md` — structured paper/report draft
|
||||||
|
- `slides.md` — slide-by-slide content outline
|
||||||
|
- `speaker-notes.md` — presenter script notes
|
||||||
|
- `insights.md` — key insights + plot interpretations (`v3` / `v4`)
|
||||||
|
- `deck.html` — printable deck HTML
|
||||||
|
- `bundle.json` — machine-readable manifest with `level` and `levelNote`
|
||||||
|
|
||||||
|
Optional local export:
|
||||||
|
- `export_pdf.py` — export `deck.html` to PDF via local headless Chromium
|
||||||
|
|
||||||
|
## Workflow
|
||||||
|
|
||||||
|
1. Point the generator at an analysis artifact directory.
|
||||||
|
2. Pass `--mode` for audience style.
|
||||||
|
3. Pass `--level` for workflow depth.
|
||||||
|
4. Review the generated markdown/html.
|
||||||
|
5. If needed, refine wording or structure.
|
||||||
|
6. If using `v4`, export `deck.html` to PDF.
|
||||||
|
|
||||||
|
## Commands
|
||||||
|
|
||||||
|
### V2 — 基礎交付版
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 {baseDir}/scripts/generate_bundle.py \
|
||||||
|
--analysis-dir /path/to/analysis/out \
|
||||||
|
--output-dir /path/to/paper-slides-out \
|
||||||
|
--title "研究標題" \
|
||||||
|
--audience "投資人" \
|
||||||
|
--purpose "簡報" \
|
||||||
|
--mode business \
|
||||||
|
--level v2
|
||||||
|
```
|
||||||
|
|
||||||
|
### V3 — 洞察強化版
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 {baseDir}/scripts/generate_bundle.py \
|
||||||
|
--analysis-dir /path/to/analysis/out \
|
||||||
|
--output-dir /path/to/paper-slides-out \
|
||||||
|
--title "研究標題" \
|
||||||
|
--audience "研究者" \
|
||||||
|
--purpose "研究整理" \
|
||||||
|
--mode academic \
|
||||||
|
--level v3
|
||||||
|
```
|
||||||
|
|
||||||
|
### V4 — 正式交付版
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 {baseDir}/scripts/generate_bundle.py \
|
||||||
|
--analysis-dir /path/to/analysis/out \
|
||||||
|
--output-dir /path/to/paper-slides-out \
|
||||||
|
--title "研究標題" \
|
||||||
|
--audience "投資人" \
|
||||||
|
--purpose "募資簡報" \
|
||||||
|
--mode pitch \
|
||||||
|
--level v4
|
||||||
|
```
|
||||||
|
|
||||||
|
## PDF export
|
||||||
|
|
||||||
|
If local Chromium is available, try:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
python3 {baseDir}/scripts/export_pdf.py \
|
||||||
|
--html /path/to/deck.html \
|
||||||
|
--pdf /path/to/deck.pdf
|
||||||
|
```
|
||||||
|
|
||||||
|
## Notes
|
||||||
|
|
||||||
|
- Prefer this skill after `code-interpreter` or any workflow that already produced plots and structured summaries.
|
||||||
|
- Keep this as a first-pass drafting tool; the output is meant to be edited, not treated as final publication-ready text.
|
||||||
|
- On this workstation, Chromium CLI `--print-to-pdf` may still fail with host-specific permission/runtime quirks even when directories are writable.
|
||||||
|
- When the user wants a PDF, try `export_pdf.py` first; if it fails, immediately fall back to OpenClaw browser PDF export on a locally served `deck.html`.
|
||||||
14
skills/research-to-paper-slides/references/pdf-notes.md
Normal file
14
skills/research-to-paper-slides/references/pdf-notes.md
Normal file
@@ -0,0 +1,14 @@
|
|||||||
|
# PDF Notes
|
||||||
|
|
||||||
|
## Current recommended path
|
||||||
|
|
||||||
|
1. Generate `deck.html` with this skill.
|
||||||
|
2. Open `deck.html` in the browser.
|
||||||
|
3. Export to PDF with browser print/PDF flow.
|
||||||
|
4. If small textual tweaks are needed after PDF export, use the installed `nano-pdf` skill.
|
||||||
|
|
||||||
|
## Why this path
|
||||||
|
|
||||||
|
- HTML is easier to iterate than direct PDF generation.
|
||||||
|
- Existing plot PNG files can be embedded cleanly.
|
||||||
|
- Browser PDF export preserves layout reliably for first-pass decks.
|
||||||
Binary file not shown.
Binary file not shown.
53
skills/research-to-paper-slides/scripts/export_pdf.py
Normal file
53
skills/research-to-paper-slides/scripts/export_pdf.py
Normal file
@@ -0,0 +1,53 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
import argparse
|
||||||
|
import glob
|
||||||
|
import os
|
||||||
|
import shutil
|
||||||
|
import subprocess
|
||||||
|
import tempfile
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
|
||||||
|
def find_browser() -> str:
|
||||||
|
# Playwright Chromium (most reliable on this workstation)
|
||||||
|
for pw in sorted(glob.glob(os.path.expanduser('~/.cache/ms-playwright/chromium-*/chrome-linux/chrome')), reverse=True):
|
||||||
|
if os.access(pw, os.X_OK):
|
||||||
|
return pw
|
||||||
|
for name in ['chromium-browser', 'chromium', 'google-chrome', 'google-chrome-stable']:
|
||||||
|
path = shutil.which(name)
|
||||||
|
if path:
|
||||||
|
return path
|
||||||
|
raise SystemExit('No supported browser found for PDF export. Install Playwright Chromium: npx playwright install chromium')
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> int:
|
||||||
|
parser = argparse.ArgumentParser(description='Export deck HTML to PDF using headless Chromium')
|
||||||
|
parser.add_argument('--html', required=True)
|
||||||
|
parser.add_argument('--pdf', required=True)
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
html_path = Path(args.html).expanduser().resolve()
|
||||||
|
pdf_path = Path(args.pdf).expanduser().resolve()
|
||||||
|
pdf_path.parent.mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
if not html_path.exists():
|
||||||
|
raise SystemExit(f'Missing HTML input: {html_path}')
|
||||||
|
|
||||||
|
browser = find_browser()
|
||||||
|
with tempfile.TemporaryDirectory(prefix='rtps-chromium-') as profile_dir:
|
||||||
|
cmd = [
|
||||||
|
browser,
|
||||||
|
'--headless',
|
||||||
|
'--disable-gpu',
|
||||||
|
'--no-sandbox',
|
||||||
|
f'--user-data-dir={profile_dir}',
|
||||||
|
f'--print-to-pdf={pdf_path}',
|
||||||
|
html_path.as_uri(),
|
||||||
|
]
|
||||||
|
subprocess.run(cmd, check=True)
|
||||||
|
print(str(pdf_path))
|
||||||
|
return 0
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
raise SystemExit(main())
|
||||||
498
skills/research-to-paper-slides/scripts/generate_bundle.py
Normal file
498
skills/research-to-paper-slides/scripts/generate_bundle.py
Normal file
@@ -0,0 +1,498 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import html
|
||||||
|
import shutil
|
||||||
|
from pathlib import Path
|
||||||
|
from typing import Any
|
||||||
|
|
||||||
|
|
||||||
|
MODES = {'academic', 'business', 'pitch'}
|
||||||
|
LEVELS = {'v2', 'v3', 'v4'}
|
||||||
|
LEVEL_NOTES = {
|
||||||
|
'v2': '基礎交付版：paper/slides/speaker-notes/deck',
|
||||||
|
'v3': '洞察強化版：v2 + insights + 每張圖逐頁解讀',
|
||||||
|
'v4': '正式交付版：v3 + 更正式 deck 視覺 + PDF-ready 工作流',
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def read_json(path: Path) -> dict[str, Any]:
|
||||||
|
return json.loads(path.read_text(encoding='utf-8'))
|
||||||
|
|
||||||
|
|
||||||
|
def read_text(path: Path) -> str:
|
||||||
|
return path.read_text(encoding='utf-8')
|
||||||
|
|
||||||
|
|
||||||
|
def find_plots(analysis_dir: Path) -> list[Path]:
|
||||||
|
return sorted([p for p in analysis_dir.glob('*.png') if p.is_file()])
|
||||||
|
|
||||||
|
|
||||||
|
def build_key_findings(summary: dict[str, Any]) -> list[str]:
|
||||||
|
findings: list[str] = []
|
||||||
|
for name, meta in summary.get('columnProfiles', {}).items():
|
||||||
|
if 'mean' in meta and meta.get('mean') is not None:
|
||||||
|
findings.append(f"欄位「{name}」平均值約為 {meta['mean']:.2f}，總和約為 {meta['sum']:.2f}。")
|
||||||
|
elif meta.get('topValues'):
|
||||||
|
top = meta['topValues'][0]
|
||||||
|
findings.append(f"欄位「{name}」最常見值為「{top['value']}」，出現 {top['count']} 次。")
|
||||||
|
if len(findings) >= 6:
|
||||||
|
break
|
||||||
|
if not findings:
|
||||||
|
findings.append('資料已完成初步整理，但尚缺少足夠特徵以自動歸納具體發現。')
|
||||||
|
return findings
|
||||||
|
|
||||||
|
|
||||||
|
def build_method_text(summary: dict[str, Any]) -> str:
|
||||||
|
rows = summary.get('rows', 0)
|
||||||
|
cols = summary.get('columns', 0)
|
||||||
|
parsed_dates = summary.get('parsedDateColumns', [])
|
||||||
|
parts = [f"本研究以一份包含 {rows} 筆資料、{cols} 個欄位的資料集作為分析基礎。"]
|
||||||
|
if parsed_dates:
|
||||||
|
parts.append(f"其中已自動辨識日期欄位：{', '.join(parsed_dates)}。")
|
||||||
|
parts.append("分析流程包含欄位剖析、數值摘要、類別分布觀察，以及圖表化初步探索。")
|
||||||
|
return ''.join(parts)
|
||||||
|
|
||||||
|
|
||||||
|
def build_limitations(summary: dict[str, Any], mode: str) -> list[str]:
|
||||||
|
base = [
|
||||||
|
'本版本內容依據自動分析結果生成，仍需依情境補充背景、語境與論證細節。',
|
||||||
|
'目前主要反映描述性分析與初步視覺化結果，尚未自動進行嚴格因果推論或完整驗證。',
|
||||||
|
]
|
||||||
|
if mode == 'pitch':
|
||||||
|
base[0] = '本版本適合作為提案底稿，但對外簡報前仍需補上商業敘事、案例與風險說明。'
|
||||||
|
elif mode == 'business':
|
||||||
|
base[0] = '本版本可支援內部決策討論，但正式匯報前仍建議補充商務脈絡與對照基準。'
|
||||||
|
elif mode == 'academic':
|
||||||
|
base[0] = '本版本可作為論文或研究報告草稿，但正式提交前仍需補足文獻回顧、研究問題與方法論細節。'
|
||||||
|
if not summary.get('plots'):
|
||||||
|
base.append('本次分析未包含圖表產物，因此視覺化證據仍需後續補充。')
|
||||||
|
return base
|
||||||
|
|
||||||
|
|
||||||
|
def classify_plot(name: str) -> str:
|
||||||
|
low = name.lower()
|
||||||
|
if low.startswith('hist_'):
|
||||||
|
return 'histogram'
|
||||||
|
if low.startswith('bar_'):
|
||||||
|
return 'bar'
|
||||||
|
if low.startswith('line_'):
|
||||||
|
return 'line'
|
||||||
|
return 'plot'
|
||||||
|
|
||||||
|
|
||||||
|
def interpret_plot(plot: Path, mode: str) -> dict[str, str]:
|
||||||
|
kind = classify_plot(plot.name)
|
||||||
|
base = {
|
||||||
|
'histogram': {
|
||||||
|
'title': f'圖表解讀：{plot.name}',
|
||||||
|
'summary': '這張 histogram 用來觀察數值欄位的分布狀態、集中區域與可能的離群位置。',
|
||||||
|
'so_what': '若資料分布偏斜或過度集中，後續可考慮分群、分層或補充異常值檢查。',
|
||||||
|
},
|
||||||
|
'bar': {
|
||||||
|
'title': f'圖表解讀：{plot.name}',
|
||||||
|
'summary': '這張 bar chart 適合比較不同類別或分組之間的量體差異，幫助快速辨識高低落差。',
|
||||||
|
'so_what': '若類別差異明顯，後續可針對高表現或低表現組別追查原因與策略。',
|
||||||
|
},
|
||||||
|
'line': {
|
||||||
|
'title': f'圖表解讀：{plot.name}',
|
||||||
|
'summary': '這張 line chart 用於觀察時間序列變化，幫助辨識趨勢、波動與可能轉折點。',
|
||||||
|
'so_what': '若趨勢持續上升或下降，建議進一步比對外部事件、季節性與干預因素。',
|
||||||
|
},
|
||||||
|
'plot': {
|
||||||
|
'title': f'圖表解讀：{plot.name}',
|
||||||
|
'summary': '這張圖表提供一個視覺化切面，有助於快速掌握資料重點與分布特徵。',
|
||||||
|
'so_what': '建議將圖表與主要論點對齊，補上更具體的背景解讀。',
|
||||||
|
},
|
||||||
|
}[kind]
|
||||||
|
|
||||||
|
if mode == 'pitch':
|
||||||
|
base['so_what'] = '簡報時應直接說明這張圖支持了哪個主張，以及它如何增加說服力。'
|
||||||
|
elif mode == 'business':
|
||||||
|
base['so_what'] = '建議把這張圖對應到 KPI、風險或下一步行動，方便管理層做判斷。'
|
||||||
|
elif mode == 'academic':
|
||||||
|
base['so_what'] = '建議將這張圖與研究問題、假設或比較基準一起討論，以提升論證完整度。'
|
||||||
|
return base
|
||||||
|
|
||||||
|
|
||||||
|
def build_insights(summary: dict[str, Any], plots: list[Path], mode: str) -> list[str]:
|
||||||
|
insights: list[str] = []
|
||||||
|
numeric = []
|
||||||
|
categorical = []
|
||||||
|
for name, meta in summary.get('columnProfiles', {}).items():
|
||||||
|
if 'mean' in meta and meta.get('mean') is not None:
|
||||||
|
numeric.append((name, meta))
|
||||||
|
elif meta.get('topValues'):
|
||||||
|
categorical.append((name, meta))
|
||||||
|
|
||||||
|
for name, meta in numeric[:3]:
|
||||||
|
insights.append(f"數值欄位「{name}」平均約 {meta['mean']:.2f}，範圍約 {meta['min']:.2f} 到 {meta['max']:.2f}。")
|
||||||
|
for name, meta in categorical[:2]:
|
||||||
|
top = meta['topValues'][0]
|
||||||
|
insights.append(f"類別欄位「{name}」目前以「{top['value']}」最常見（{top['count']} 次），值得作為第一輪聚焦對象。")
|
||||||
|
if plots:
|
||||||
|
insights.append(f"本次已生成 {len(plots)} 張圖表，可直接支撐逐頁圖表解讀與口頭報告。")
|
||||||
|
|
||||||
|
if mode == 'pitch':
|
||||||
|
insights.append('對外提案時，建議把最強的一項數據證據前置，讓聽眾先記住價值主張。')
|
||||||
|
elif mode == 'business':
|
||||||
|
insights.append('內部決策簡報時，建議把洞察轉成 KPI、優先順序與負責人。')
|
||||||
|
elif mode == 'academic':
|
||||||
|
insights.append('學術/研究情境下，建議將洞察進一步轉成研究問題、比較架構與後續驗證方向。')
|
||||||
|
return insights
|
||||||
|
|
||||||
|
|
||||||
|
def make_insights_md(title: str, mode: str, summary: dict[str, Any], plots: list[Path]) -> str:
|
||||||
|
insights = build_insights(summary, plots, mode)
|
||||||
|
plot_notes = [interpret_plot(p, mode) for p in plots]
|
||||||
|
lines = [f"# {title}｜Insights", '', f"- 模式：`{mode}`", '']
|
||||||
|
lines.append('## 關鍵洞察')
|
||||||
|
lines.extend([f"- {x}" for x in insights])
|
||||||
|
lines.append('')
|
||||||
|
if plot_notes:
|
||||||
|
lines.append('## 圖表解讀摘要')
|
||||||
|
for note in plot_notes:
|
||||||
|
lines.append(f"### {note['title']}")
|
||||||
|
lines.append(f"- 解讀：{note['summary']}")
|
||||||
|
lines.append(f"- 延伸：{note['so_what']}")
|
||||||
|
lines.append('')
|
||||||
|
return '\n'.join(lines).strip() + '\n'
|
||||||
|
|
||||||
|
|
||||||
|
def make_paper(title: str, audience: str, purpose: str, mode: str, level: str, summary: dict[str, Any], report_md: str, plots: list[Path], insights_md: str | None = None) -> str:
|
||||||
|
findings = build_key_findings(summary)
|
||||||
|
method_text = build_method_text(summary)
|
||||||
|
limitations = build_limitations(summary, mode)
|
||||||
|
plot_refs = '\n'.join([f"- `{p.name}`" for p in plots]) or '- 無'
|
||||||
|
findings_md = '\n'.join([f"- {x}" for x in findings])
|
||||||
|
limitations_md = '\n'.join([f"- {x}" for x in limitations])
|
||||||
|
|
||||||
|
if mode == 'academic':
|
||||||
|
sections = f"## 摘要\n\n本文面向{audience}，以「{purpose}」為導向，整理目前資料分析結果並形成學術/研究草稿。\n\n## 研究背景與問題意識\n\n本文件根據既有分析產物自動整理，可作為研究報告、論文初稿或研究提案的起點。\n\n## 研究方法\n\n{method_text}\n\n## 研究發現\n\n{findings_md}\n\n## 討論\n\n目前結果可支撐初步描述性討論，後續可進一步補上研究假設、比較對照與方法嚴謹性。\n\n## 限制\n\n{limitations_md}\n\n## 結論\n\n本分析已形成研究性文件的結構基礎，適合進一步擴展為正式研究報告。"
|
||||||
|
elif mode == 'business':
|
||||||
|
sections = f"## 執行摘要\n\n本文面向{audience}，目的是支援「{purpose}」的商務溝通與內部決策。\n\n## 商務背景\n\n本文件根據既有分析產物自動整理，適合作為內部簡報、策略討論或管理層報告的第一版。\n\n## 分析方法\n\n{method_text}\n\n## 關鍵洞察\n\n{findings_md}\n\n## 商業意涵\n\n目前資料已足以支撐一輪決策討論，建議進一步對照 KPI、目標值與外部環境。\n\n## 風險與限制\n\n{limitations_md}\n\n## 建議下一步\n\n建議針對最具決策價值的指標建立定期追蹤與後續驗證流程。"
|
||||||
|
else:
|
||||||
|
sections = f"## Pitch Summary\n\n本文面向{audience}，用於支援「{purpose}」的提案、募資或說服型簡報。\n\n## Opportunity\n\n本文件根據既有分析產物自動整理，可作為提案 deck 與口頭簡報的第一版底稿。\n\n## Evidence\n\n{method_text}\n\n## Key Takeaways\n\n{findings_md}\n\n## Why It Matters\n\n目前結果已可形成明確敘事雛形，後續可補上市場機會、競品比較與具體行動方案。\n\n## Risks\n\n{limitations_md}\n\n## Ask / Next Step\n\n建議將數據證據、主張與下一步行動整合成對外一致的提案版本。"
|
||||||
|
|
||||||
|
insight_section = ''
|
||||||
|
if insights_md:
|
||||||
|
insight_section = f"\n## 洞察摘要\n\n{insights_md}\n"
|
||||||
|
|
||||||
|
return f"# {title}\n\n- 模式：`{mode}`\n- 等級：`{level}` — {LEVEL_NOTES[level]}\n- 對象：{audience}\n- 目的：{purpose}\n\n{sections}\n\n## 圖表與視覺化資產\n\n{plot_refs}{insight_section}\n## 附錄：原始自動分析摘要\n\n{report_md}\n"
|
||||||
|
|
||||||
|
|
||||||
|
def make_slides(title: str, audience: str, purpose: str, mode: str, summary: dict[str, Any], plots: list[Path], level: str) -> str:
|
||||||
|
findings = build_key_findings(summary)
|
||||||
|
rows = summary.get('rows', 0)
|
||||||
|
cols = summary.get('columns', 0)
|
||||||
|
|
||||||
|
if mode == 'academic':
|
||||||
|
slides = [
|
||||||
|
('封面', [f'標題：{title}', f'對象：{audience}', f'目的：{purpose}', f'等級：{LEVEL_NOTES[level]}']),
|
||||||
|
('研究問題', ['定義研究背景與核心問題', '說明本次分析欲回答的主題']),
|
||||||
|
('資料概況', [f'資料筆數：{rows}', f'欄位數：{cols}', '已完成基本欄位剖析與摘要']),
|
||||||
|
('方法', ['描述性統計', '類別分布觀察', '視覺化探索']),
|
||||||
|
('研究發現', findings[:3]),
|
||||||
|
('討論', ['解釋主要發現的可能意義', '連結研究問題與資料結果']),
|
||||||
|
('限制', build_limitations(summary, mode)[:2]),
|
||||||
|
('後續研究', ['補充文獻回顧', '加入比較基準與進階分析']),
|
||||||
|
('結論', ['本份簡報可作為研究報告或論文簡報的第一版底稿']),
|
||||||
|
]
|
||||||
|
elif mode == 'business':
|
||||||
|
slides = [
|
||||||
|
('封面', [f'標題：{title}', f'對象：{audience}', f'目的：{purpose}', f'等級：{LEVEL_NOTES[level]}']),
|
||||||
|
('決策問題', ['這份分析要支援什麼決策', '為什麼現在需要處理']),
|
||||||
|
('資料概況', [f'資料筆數：{rows}', f'欄位數：{cols}', '已完成基本資料盤點']),
|
||||||
|
('分析方法', ['描述性統計', '類別分布觀察', '視覺化探索']),
|
||||||
|
('關鍵洞察', findings[:3]),
|
||||||
|
('商業意涵', ['把數據結果轉成管理層可理解的含義', '指出可能影響的目標或 KPI']),
|
||||||
|
('風險與限制', build_limitations(summary, mode)[:2]),
|
||||||
|
('建議行動', ['列出近期可執行事項', '定義需要追蹤的指標']),
|
||||||
|
('結語', ['本份簡報可作為正式管理簡報的第一版底稿']),
|
||||||
|
]
|
||||||
|
else:
|
||||||
|
slides = [
|
||||||
|
('封面', [f'標題：{title}', f'對象：{audience}', f'目的：{purpose}', f'等級：{LEVEL_NOTES[level]}']),
|
||||||
|
('痛點 / 機會', ['說明這份分析解決什麼問題', '點出為什麼值得關注']),
|
||||||
|
('證據基礎', [f'資料筆數：{rows}', f'欄位數：{cols}', '已完成資料摘要與圖表探索']),
|
||||||
|
('方法', ['描述性統計', '類別觀察', '關鍵圖表整理']),
|
||||||
|
('核心亮點', findings[:3]),
|
||||||
|
('為什麼重要', ['連結價值、影響與說服力', '把發現轉成可傳達的敘事']),
|
||||||
|
('風險', build_limitations(summary, mode)[:2]),
|
||||||
|
('Next Step / Ask', ['明確提出下一步', '對齊資源、合作或決策需求']),
|
||||||
|
('結語', ['本份 deck 可作為提案或募資簡報的第一版底稿']),
|
||||||
|
]
|
||||||
|
|
||||||
|
parts = [f"# {title}｜簡報稿\n\n- 模式：`{mode}`\n- 等級：`{level}` — {LEVEL_NOTES[level]}\n"]
|
||||||
|
slide_no = 1
|
||||||
|
for heading, bullets in slides:
|
||||||
|
parts.append(f"## Slide {slide_no} — {heading}")
|
||||||
|
parts.extend([f"- {x}" for x in bullets])
|
||||||
|
parts.append('')
|
||||||
|
slide_no += 1
|
||||||
|
|
||||||
|
if level in {'v3', 'v4'} and plots:
|
||||||
|
for plot in plots:
|
||||||
|
note = interpret_plot(plot, mode)
|
||||||
|
parts.append(f"## Slide {slide_no} — {note['title']}")
|
||||||
|
parts.append(f"- 圖檔：{plot.name}")
|
||||||
|
parts.append(f"- 解讀：{note['summary']}")
|
||||||
|
parts.append(f"- 延伸：{note['so_what']}")
|
||||||
|
parts.append('')
|
||||||
|
slide_no += 1
|
||||||
|
return '\n'.join(parts).strip() + '\n'
|
||||||
|
|
||||||
|
|
||||||
|
def make_speaker_notes(title: str, mode: str, summary: dict[str, Any], plots: list[Path], level: str) -> str:
|
||||||
|
findings = build_key_findings(summary)
|
||||||
|
findings_md = '\n'.join([f"- {x}" for x in findings])
|
||||||
|
opener = {
|
||||||
|
'academic': '先交代研究背景、研究問題與資料來源，再說明這份內容是研究草稿第一版。',
|
||||||
|
'business': '先講這份分析支援哪個決策，再交代這份內容的管理價值與時間敏感性。',
|
||||||
|
'pitch': '先抓住聽眾注意力，說明痛點、機會與這份資料為何值得相信。',
|
||||||
|
}[mode]
|
||||||
|
closer = {
|
||||||
|
'academic': '結尾時回到研究限制與後續研究方向。',
|
||||||
|
'business': '結尾時回到建議行動與追蹤機制。',
|
||||||
|
'pitch': '結尾時回到 ask、資源需求與下一步承諾。',
|
||||||
|
}[mode]
|
||||||
|
parts = [
|
||||||
|
f"# {title}｜Speaker Notes",
|
||||||
|
'',
|
||||||
|
f"- 模式：`{mode}`",
|
||||||
|
f"- 等級：`{level}` — {LEVEL_NOTES[level]}",
|
||||||
|
'',
|
||||||
|
'## 開場',
|
||||||
|
f"- {opener}",
|
||||||
|
'',
|
||||||
|
'## 重點提示',
|
||||||
|
findings_md,
|
||||||
|
'',
|
||||||
|
]
|
||||||
|
if level in {'v3', 'v4'} and plots:
|
||||||
|
parts.extend(['## 逐圖口頭提示', ''])
|
||||||
|
for plot in plots:
|
||||||
|
note = interpret_plot(plot, mode)
|
||||||
|
parts.append(f"### {plot.name}")
|
||||||
|
parts.append(f"- {note['summary']}")
|
||||||
|
parts.append(f"- {note['so_what']}")
|
||||||
|
parts.append('')
|
||||||
|
parts.extend(['## 收尾建議', f"- {closer}", '- 針對最重要的一張圖，多講一層其背後的意義與行動建議。', ''])
|
||||||
|
return '\n'.join(parts)
|
||||||
|
|
||||||
|
|
||||||
|
def make_deck_html(title: str, audience: str, purpose: str, slides_md: str, plots: list[Path], mode: str, level: str) -> str:
|
||||||
|
if level == 'v4':
|
||||||
|
theme = {
|
||||||
|
'academic': {'primary': '#0f172a', 'accent': '#334155', 'bg': '#eef2ff', 'hero': 'linear-gradient(135deg,#0f172a 0%,#1e293b 55%,#475569 100%)'},
|
||||||
|
'business': {'primary': '#0b3b66', 'accent': '#1d4ed8', 'bg': '#eff6ff', 'hero': 'linear-gradient(135deg,#0b3b66 0%,#1d4ed8 60%,#60a5fa 100%)'},
|
||||||
|
'pitch': {'primary': '#4c1d95', 'accent': '#7c3aed', 'bg': '#faf5ff', 'hero': 'linear-gradient(135deg,#4c1d95 0%,#7c3aed 60%,#c084fc 100%)'},
|
||||||
|
}[mode]
|
||||||
|
primary = theme['primary']
|
||||||
|
accent = theme['accent']
|
||||||
|
bg = theme['bg']
|
||||||
|
hero = theme['hero']
|
||||||
|
plot_map = {p.name: p for p in plots}
|
||||||
|
else:
|
||||||
|
primary = '#1f2937'
|
||||||
|
accent = '#2563eb'
|
||||||
|
bg = '#f6f8fb'
|
||||||
|
hero = None
|
||||||
|
plot_map = {p.name: p for p in plots}
|
||||||
|
|
||||||
|
slide_blocks = []
|
||||||
|
current = []
|
||||||
|
current_title = None
|
||||||
|
for line in slides_md.splitlines():
|
||||||
|
if line.startswith('## Slide '):
|
||||||
|
if current_title is not None:
|
||||||
|
slide_blocks.append((current_title, current))
|
||||||
|
current_title = line.replace('## ', '', 1)
|
||||||
|
current = []
|
||||||
|
elif line.startswith('- 模式：') or line.startswith('- 等級：') or line.startswith('# '):
|
||||||
|
continue
|
||||||
|
else:
|
||||||
|
current.append(line)
|
||||||
|
if current_title is not None:
|
||||||
|
slide_blocks.append((current_title, current))
|
||||||
|
|
||||||
|
sections = []
|
||||||
|
for heading, body in slide_blocks:
|
||||||
|
body_html = []
|
||||||
|
referenced_plot = None
|
||||||
|
for line in body:
|
||||||
|
line = line.strip()
|
||||||
|
if not line:
|
||||||
|
continue
|
||||||
|
if line.startswith('- 圖檔：'):
|
||||||
|
plot_name = line.replace('- 圖檔：', '', 1).strip()
|
||||||
|
referenced_plot = plot_map.get(plot_name)
|
||||||
|
body_html.append(f"<li>{html.escape(line[2:])}</li>")
|
||||||
|
elif line.startswith('- '):
|
||||||
|
body_html.append(f"<li>{html.escape(line[2:])}</li>")
|
||||||
|
else:
|
||||||
|
body_html.append(f"<p>{html.escape(line)}</p>")
|
||||||
|
img_html = ''
|
||||||
|
if referenced_plot and level in {'v3', 'v4'}:
|
||||||
|
img_html = f"<div class='plot-single'><img src='{html.escape(referenced_plot.name)}' alt='{html.escape(referenced_plot.name)}' /><div class='plot-caption'>圖：{html.escape(referenced_plot.name)}</div></div>"
|
||||||
|
list_items = ''.join(x for x in body_html if x.startswith('<li>'))
|
||||||
|
paras = ''.join(x for x in body_html if x.startswith('<p>'))
|
||||||
|
list_html = f"<ul>{list_items}</ul>" if list_items else ''
|
||||||
|
if level == 'v4':
|
||||||
|
sections.append(
|
||||||
|
f"<section class='slide'><div class='slide-top'><div class='eyebrow'>{html.escape(mode.upper())}</div>"
|
||||||
|
f"<div class='page-tag'>{html.escape(heading.split(' — ')[0])}</div></div><h2>{html.escape(heading)}</h2>{paras}{list_html}{img_html}</section>"
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
sections.append(f"<section class='slide'><h2>{html.escape(heading)}</h2>{paras}{list_html}{img_html}</section>")
|
||||||
|
|
||||||
|
if level == 'v4':
|
||||||
|
css = f"""
|
||||||
|
@page {{ size: A4 landscape; margin: 0; }}
|
||||||
|
@media print {{
|
||||||
|
body {{ background: #fff; padding: 0; }}
|
||||||
|
.slide {{ box-shadow: none; margin: 0; min-height: 100vh; border-radius: 0; page-break-after: always; page-break-inside: avoid; border-top-width: 16px; border-top-style: solid; border-top-color: {accent}; }}
|
||||||
|
.hero {{ box-shadow: none; margin: 0; min-height: 100vh; border-radius: 0; }}
|
||||||
|
}}
|
||||||
|
body {{ font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, 'Noto Sans CJK TC', sans-serif; background: {bg}; margin: 0; padding: 32px; color: {primary}; }}
|
||||||
|
.hero {{ max-width: 1180px; margin: 0 auto 32px; padding: 56px 64px; border-radius: 32px; background: {hero}; color: white; box-shadow: 0 32px 64px rgba(15,23,42,.15); display: flex; flex-direction: column; justify-content: center; min-height: 500px; }}
|
||||||
|
.hero h1 {{ margin: 12px 0 20px; font-size: 52px; line-height: 1.2; letter-spacing: -0.02em; font-weight: 800; text-wrap: balance; }}
|
||||||
|
.hero p {{ margin: 8px 0; font-size: 20px; opacity: .9; font-weight: 400; }}
|
||||||
|
.hero-meta {{ display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 16px; margin-top: 48px; }}
|
||||||
|
.hero-card {{ background: rgba(255,255,255,.1); border: 1px solid rgba(255,255,255,.2); border-radius: 20px; padding: 20px 24px; backdrop-filter: blur(10px); }}
|
||||||
|
.hero-card strong {{ display: block; font-size: 14px; text-transform: uppercase; letter-spacing: 0.05em; opacity: 0.8; margin-bottom: 6px; }}
|
||||||
|
.slide {{ background: #fff; border-radius: 32px; padding: 48px 56px; margin: 0 auto 32px; max-width: 1180px; min-height: 660px; box-shadow: 0 16px 48px rgba(15,23,42,.08); page-break-after: always; border-top: 16px solid {accent}; position: relative; overflow: hidden; display: flex; flex-direction: column; }}
|
||||||
|
.slide::after {{ content: ''; position: absolute; right: -80px; top: -80px; width: 240px; height: 240px; background: radial-gradient(circle, {bg} 0%, rgba(255,255,255,0) 70%); pointer-events: none; }}
|
||||||
|
.slide-top {{ display: flex; justify-content: space-between; align-items: center; margin-bottom: 24px; z-index: 1; }}
|
||||||
|
h1, h2 {{ margin-top: 0; font-weight: 700; }}
|
||||||
|
h2 {{ font-size: 36px; margin-bottom: 24px; color: {primary}; letter-spacing: -0.01em; }}
|
||||||
|
.slide p {{ font-size: 20px; line-height: 1.6; color: #334155; margin-bottom: 16px; }}
|
||||||
|
.slide ul {{ line-height: 1.6; font-size: 22px; padding-left: 28px; color: #1e293b; margin-top: 8px; flex-grow: 1; }}
|
||||||
|
.slide li {{ position: relative; padding-left: 8px; }}
|
||||||
|
.slide li + li {{ margin-top: 14px; }}
|
||||||
|
.slide li::marker {{ color: {accent}; font-weight: bold; }}
|
||||||
|
.eyebrow {{ display: inline-flex; align-items: center; padding: 8px 16px; border-radius: 999px; background: {bg}; color: {accent}; font-weight: 800; font-size: 13px; letter-spacing: .1em; box-shadow: 0 2px 8px rgba(0,0,0,0.04); }}
|
||||||
|
.page-tag {{ color: #94a3b8; font-size: 14px; font-weight: 700; text-transform: uppercase; letter-spacing: 0.05em; }}
|
||||||
|
.plot-single {{ margin-top: auto; text-align: center; padding-top: 24px; position: relative; display: flex; flex-direction: column; align-items: center; justify-content: center; }}
|
||||||
|
.plot-single img {{ max-width: 100%; max-height: 380px; border: 1px solid #e2e8f0; border-radius: 20px; background: #f8fafc; box-shadow: 0 12px 32px rgba(15,23,42,.06); padding: 8px; }}
|
||||||
|
.plot-caption {{ margin-top: 14px; font-size: 15px !important; color: #64748b !important; font-style: italic; text-align: center; background: #f1f5f9; padding: 6px 16px; border-radius: 999px; }}
|
||||||
|
""".strip()
|
||||||
|
hero_html = (
|
||||||
|
f"<div class='hero'><div class='eyebrow'>{html.escape(mode.upper())}</div>"
|
||||||
|
f"<h1>{html.escape(title)}</h1><p>適用對象：{html.escape(audience)}</p><p>目的：{html.escape(purpose)}</p>"
|
||||||
|
f"<div class='hero-meta'>"
|
||||||
|
f"<div class='hero-card'><strong>等級</strong><br>{html.escape(level)} — {html.escape(LEVEL_NOTES[level])}</div>"
|
||||||
|
f"<div class='hero-card'><strong>圖表數量</strong><br>{len(plots)}</div>"
|
||||||
|
f"<div class='hero-card'><strong>輸出定位</strong><br>正式 deck / PDF-ready</div>"
|
||||||
|
f"</div></div>"
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
css = f"""
|
||||||
|
body {{ font-family: Arial, 'Noto Sans CJK TC', sans-serif; background: {bg}; margin: 0; padding: 24px; color: {primary}; }}
|
||||||
|
.hero {{ max-width: 1100px; margin: 0 auto 24px; padding: 8px 6px; }}
|
||||||
|
.slide {{ background: #fff; border-radius: 18px; padding: 32px; margin: 0 auto 24px; max-width: 1100px; box-shadow: 0 8px 28px rgba(0,0,0,.08); page-break-after: always; border-top: 10px solid {accent}; }}
|
||||||
|
h1, h2 {{ margin-top: 0; }}
|
||||||
|
h1 {{ font-size: 40px; }}
|
||||||
|
ul {{ line-height: 1.7; }}
|
||||||
|
.plot-single {{ margin-top: 18px; text-align: center; }}
|
||||||
|
img {{ max-width: 100%; border: 1px solid #ddd; border-radius: 12px; background: #fff; }}
|
||||||
|
.plot-caption {{ margin-top: 10px; font-size: 14px; color: #6b7280; font-style: italic; }}
|
||||||
|
""".strip()
|
||||||
|
hero_html = (
|
||||||
|
f"<div class='hero'><h1>{html.escape(title)}</h1><p>對象：{html.escape(audience)}</p>"
|
||||||
|
f"<p>目的：{html.escape(purpose)}</p><p>等級：{html.escape(level)} — {html.escape(LEVEL_NOTES[level])}</p></div>"
|
||||||
|
)
|
||||||
|
|
||||||
|
return (
|
||||||
|
"<!doctype html><html><head><meta charset='utf-8'>"
|
||||||
|
f"<title>{html.escape(title)}</title><style>{css}</style></head><body>"
|
||||||
|
+ hero_html
|
||||||
|
+ ''.join(sections)
|
||||||
|
+ "</body></html>"
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def main() -> int:
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description='Generate paper/slides bundle from analysis outputs',
|
||||||
|
epilog=(
|
||||||
|
'Levels: '
|
||||||
|
'v2=基礎交付版（paper/slides/speaker-notes/deck）； '
|
||||||
|
'v3=洞察強化版（v2 + insights + 每張圖逐頁解讀）； '
|
||||||
|
'v4=正式交付版（v3 + 更正式 deck 視覺 + PDF-ready 工作流）'
|
||||||
|
),
|
||||||
|
)
|
||||||
|
parser.add_argument('--analysis-dir', required=True)
|
||||||
|
parser.add_argument('--output-dir', required=True)
|
||||||
|
parser.add_argument('--title', default='研究分析草稿')
|
||||||
|
parser.add_argument('--audience', default='決策者')
|
||||||
|
parser.add_argument('--purpose', default='研究報告')
|
||||||
|
parser.add_argument('--mode', default='business', choices=sorted(MODES))
|
||||||
|
parser.add_argument(
|
||||||
|
'--level',
|
||||||
|
default='v4',
|
||||||
|
choices=sorted(LEVELS),
|
||||||
|
help='輸出等級：v2=基礎交付版；v3=洞察強化版；v4=正式交付版（預設）',
|
||||||
|
)
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
analysis_dir = Path(args.analysis_dir).expanduser().resolve()
|
||||||
|
output_dir = Path(args.output_dir).expanduser().resolve()
|
||||||
|
output_dir.mkdir(parents=True, exist_ok=True)
|
||||||
|
|
||||||
|
summary_path = analysis_dir / 'summary.json'
|
||||||
|
report_path = analysis_dir / 'report.md'
|
||||||
|
if not summary_path.exists():
|
||||||
|
raise SystemExit(f'Missing summary.json in {analysis_dir}')
|
||||||
|
if not report_path.exists():
|
||||||
|
raise SystemExit(f'Missing report.md in {analysis_dir}')
|
||||||
|
|
||||||
|
summary = read_json(summary_path)
|
||||||
|
report_md = read_text(report_path)
|
||||||
|
plots = find_plots(analysis_dir)
|
||||||
|
insights_md = make_insights_md(args.title, args.mode, summary, plots) if args.level in {'v3', 'v4'} else None
|
||||||
|
|
||||||
|
paper_md = make_paper(args.title, args.audience, args.purpose, args.mode, args.level, summary, report_md, plots, insights_md)
|
||||||
|
slides_md = make_slides(args.title, args.audience, args.purpose, args.mode, summary, plots, args.level)
|
||||||
|
speaker_notes = make_speaker_notes(args.title, args.mode, summary, plots, args.level)
|
||||||
|
deck_html = make_deck_html(args.title, args.audience, args.purpose, slides_md, plots, args.mode, args.level)
|
||||||
|
|
||||||
|
for plot in plots:
|
||||||
|
dest = output_dir / plot.name
|
||||||
|
if dest != plot:
|
||||||
|
shutil.copy2(plot, dest)
|
||||||
|
|
||||||
|
(output_dir / 'paper.md').write_text(paper_md, encoding='utf-8')
|
||||||
|
(output_dir / 'slides.md').write_text(slides_md, encoding='utf-8')
|
||||||
|
(output_dir / 'speaker-notes.md').write_text(speaker_notes, encoding='utf-8')
|
||||||
|
(output_dir / 'deck.html').write_text(deck_html, encoding='utf-8')
|
||||||
|
if insights_md:
|
||||||
|
(output_dir / 'insights.md').write_text(insights_md, encoding='utf-8')
|
||||||
|
|
||||||
|
manifest_outputs = {
|
||||||
|
'paper': str(output_dir / 'paper.md'),
|
||||||
|
'slides': str(output_dir / 'slides.md'),
|
||||||
|
'speakerNotes': str(output_dir / 'speaker-notes.md'),
|
||||||
|
'deckHtml': str(output_dir / 'deck.html'),
|
||||||
|
}
|
||||||
|
if insights_md:
|
||||||
|
manifest_outputs['insights'] = str(output_dir / 'insights.md')
|
||||||
|
|
||||||
|
manifest = {
|
||||||
|
'title': args.title,
|
||||||
|
'audience': args.audience,
|
||||||
|
'purpose': args.purpose,
|
||||||
|
'mode': args.mode,
|
||||||
|
'level': args.level,
|
||||||
|
'levelNote': LEVEL_NOTES[args.level],
|
||||||
|
'analysisDir': str(analysis_dir),
|
||||||
|
'outputs': manifest_outputs,
|
||||||
|
'plots': [str(p) for p in plots],
|
||||||
|
}
|
||||||
|
(output_dir / 'bundle.json').write_text(json.dumps(manifest, ensure_ascii=False, indent=2), encoding='utf-8')
|
||||||
|
print(json.dumps(manifest, ensure_ascii=False, indent=2))
|
||||||
|
return 0
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
raise SystemExit(main())
|
||||||
127
skills/skill-review/SKILL.md
Normal file
127
skills/skill-review/SKILL.md
Normal file
@@ -0,0 +1,127 @@
|
|||||||
|
---
|
||||||
|
name: skill-review
|
||||||
|
description: 審查 openclaw-skill repo 中的 Skills，提出改進建議並透過 Gitea PR 提交。每位 Agent 有各自的 fork，走標準 fork → branch → PR 流程。
|
||||||
|
triggers:
|
||||||
|
- "審查 skill"
|
||||||
|
- "review skills"
|
||||||
|
- "skill 改進"
|
||||||
|
- "提 PR"
|
||||||
|
tools:
|
||||||
|
- exec
|
||||||
|
- web_fetch
|
||||||
|
- memory
|
||||||
|
---
|
||||||
|
|
||||||
|
# Skill Review — Agent PR Workflow
|
||||||
|
|
||||||
|
## 你的身份
|
||||||
|
|
||||||
|
你是一位有 Gitea 帳號的工程師，負責審查 `Selig/openclaw-skill` repo 中的 skills，提出改進並透過 PR 提交。
|
||||||
|
|
||||||
|
## 環境變數
|
||||||
|
|
||||||
|
- `GITEA_URL`: Gitea 基礎 URL（https://git.nature.edu.kg）
|
||||||
|
- `GITEA_TOKEN_<AGENT>`: 你的 Gitea API token（根據 agent ID 取對應的）
|
||||||
|
- Agent → Gitea 帳號對應：
|
||||||
|
- main → `xiaoming`（小明，專案管理/綜合審查）
|
||||||
|
- tiangong → `tiangong`（天工，架構/安全）
|
||||||
|
- kaiwu → `kaiwu`（開物，UX/前端）
|
||||||
|
- yucheng → `yucheng`（玉成，全棧/測試）
|
||||||
|
|
||||||
|
## 審查重點
|
||||||
|
|
||||||
|
根據你的角色，重點審查不同面向：
|
||||||
|
|
||||||
|
### 小明（main）— 專案經理
|
||||||
|
- 整體 skill 的完整性與一致性
|
||||||
|
- SKILL.md 描述是否清楚、trigger 是否遺漏常見用法
|
||||||
|
- 跨 skill 的重複邏輯或可整合之處
|
||||||
|
- 文件與實作是否同步
|
||||||
|
|
||||||
|
### 天工（tiangong）— 架構設計師
|
||||||
|
- SKILL.md 的 trigger 設計是否合理、會不會誤觸發
|
||||||
|
- handler.ts 的錯誤處理、邊界情況
|
||||||
|
- 安全性：有無注入風險、敏感資訊洩漏
|
||||||
|
- Skill 之間的協作與依賴關係
|
||||||
|
|
||||||
|
### 開物（kaiwu）— 前端視覺
|
||||||
|
- SKILL.md 的使用者體驗：描述是否清楚、觸發詞是否直覺
|
||||||
|
- handler.ts 的輸出格式：Telegram markdown 排版、emoji 使用
|
||||||
|
- 回覆內容的可讀性與美觀度
|
||||||
|
|
||||||
|
### 玉成（yucheng）— 全棧整合
|
||||||
|
- handler.ts 的程式碼品質：型別安全、效能、可維護性
|
||||||
|
- 缺少的功能或整合機會
|
||||||
|
- 測試邊界：空值處理、異常輸入
|
||||||
|
- 文件完整性
|
||||||
|
|
||||||
|
## 工作流程
|
||||||
|
|
||||||
|
### Step 1: 同步 fork
|
||||||
|
```
|
||||||
|
POST /api/v1/repos/{owner}/{repo}/mirror-sync # 如果有 mirror
|
||||||
|
```
|
||||||
|
或者直接用最新的 upstream 內容。
|
||||||
|
|
||||||
|
### Step 2: 讀取所有 Skills
|
||||||
|
讀取 repo 中 `skills/` 目錄下的每個 skill 的 SKILL.md 和 handler.ts。
|
||||||
|
|
||||||
|
### Step 3: 選擇改進目標
|
||||||
|
- 每次只改 **1 個 skill 的 1 個面向**（小而精確的 PR）
|
||||||
|
- 如果所有 skill 都很好，可以提出新 skill 的建議
|
||||||
|
|
||||||
|
### Step 4: 透過 Gitea API 提交
|
||||||
|
|
||||||
|
1. **建立分支**（從 main）
|
||||||
|
```
|
||||||
|
POST /api/v1/repos/{owner}/{repo}/branches
|
||||||
|
{"new_branch_name": "improve/daily-briefing-error-handling", "old_branch_name": "main"}
|
||||||
|
```
|
||||||
|
|
||||||
|
2. **更新檔案**
|
||||||
|
```
|
||||||
|
PUT /api/v1/repos/{owner}/{repo}/contents/{filepath}
|
||||||
|
{"content": "<base64>", "message": "commit message", "branch": "improve/...", "sha": "<current-sha>"}
|
||||||
|
```
|
||||||
|
|
||||||
|
3. **建立 PR**（從 fork 到 upstream）
|
||||||
|
```
|
||||||
|
POST /api/v1/repos/Selig/openclaw-skill/pulls
|
||||||
|
{
|
||||||
|
"title": "improve(daily-briefing): 加強天氣查詢錯誤處理",
|
||||||
|
"body": "## 改進說明\n...\n## 變更內容\n...\n## 測試建議\n...",
|
||||||
|
"head": "<agent-username>:improve/daily-briefing-error-handling",
|
||||||
|
"base": "main"
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## PR 格式規範
|
||||||
|
|
||||||
|
### 標題
|
||||||
|
```
|
||||||
|
<type>(<skill>): <簡述>
|
||||||
|
```
|
||||||
|
Type: `improve`, `fix`, `feat`, `docs`, `refactor`
|
||||||
|
|
||||||
|
### 內文
|
||||||
|
```markdown
|
||||||
|
## 改進說明
|
||||||
|
為什麼要做這個改動？發現了什麼問題？
|
||||||
|
|
||||||
|
## 變更內容
|
||||||
|
- 具體改了什麼
|
||||||
|
|
||||||
|
## 測試建議
|
||||||
|
- 如何驗證這個改動是正確的
|
||||||
|
|
||||||
|
---
|
||||||
|
🤖 由 <agent-name> 自動審查並提交
|
||||||
|
```
|
||||||
|
|
||||||
|
## 注意事項
|
||||||
|
|
||||||
|
- **一次只提一個 PR**，不要批量修改多個 skill
|
||||||
|
- **不要修改** handler.ts 中涉及認證、密碼、token 的部分
|
||||||
|
- **不要刪除** 現有功能，只能改進或新增
|
||||||
|
- 如果沒有值得改進的地方，回覆「所有 Skills 目前狀態良好，無需改動」即可
|
||||||
|
- PR 建立後，回覆 PR 的 URL 讓使用者知道
|
||||||
241
skills/skill-review/handler.ts
Normal file
241
skills/skill-review/handler.ts
Normal file
@@ -0,0 +1,241 @@
|
|||||||
|
/**
|
||||||
|
* skill-review handler
|
||||||
|
* 提供 Gitea API 操作的輔助函式，供 agent 審查 skill 並提交 PR。
|
||||||
|
*/
|
||||||
|
|
||||||
|
const GITEA_URL = process.env.GITEA_URL || 'https://git.nature.edu.kg';
|
||||||
|
const UPSTREAM_OWNER = 'Selig';
|
||||||
|
const REPO_NAME = 'openclaw-skill';
|
||||||
|
|
||||||
|
// Agent ID → Gitea 帳號 & token 環境變數對應
|
||||||
|
const AGENT_MAP: Record<string, { username: string; tokenEnv: string }> = {
|
||||||
|
main: { username: 'xiaoming', tokenEnv: 'GITEA_TOKEN_XIAOMING' },
|
||||||
|
tiangong: { username: 'tiangong', tokenEnv: 'GITEA_TOKEN_TIANGONG' },
|
||||||
|
kaiwu: { username: 'kaiwu', tokenEnv: 'GITEA_TOKEN_KAIWU' },
|
||||||
|
yucheng: { username: 'yucheng', tokenEnv: 'GITEA_TOKEN_YUCHENG' },
|
||||||
|
};
|
||||||
|
|
||||||
|
interface GiteaFile {
|
||||||
|
name: string;
|
||||||
|
path: string;
|
||||||
|
sha: string;
|
||||||
|
content?: string;
|
||||||
|
encoding?: string;
|
||||||
|
}
|
||||||
|
|
||||||
|
async function giteaApi(
|
||||||
|
token: string,
|
||||||
|
method: string,
|
||||||
|
path: string,
|
||||||
|
body?: any
|
||||||
|
): Promise<any> {
|
||||||
|
const url = `${GITEA_URL}/api/v1${path}`;
|
||||||
|
const opts: RequestInit = {
|
||||||
|
method,
|
||||||
|
headers: {
|
||||||
|
Authorization: `token ${token}`,
|
||||||
|
'Content-Type': 'application/json',
|
||||||
|
},
|
||||||
|
};
|
||||||
|
if (body) opts.body = JSON.stringify(body);
|
||||||
|
const res = await fetch(url, opts);
|
||||||
|
const text = await res.text();
|
||||||
|
if (!res.ok) {
|
||||||
|
throw new Error(`Gitea API ${method} ${path} → ${res.status}: ${text}`);
|
||||||
|
}
|
||||||
|
return text ? JSON.parse(text) : null;
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 同步 fork（用 Gitea merge upstream API） */
|
||||||
|
async function syncFork(token: string, owner: string): Promise<void> {
|
||||||
|
try {
|
||||||
|
// Gitea 1.25: POST /repos/{owner}/{repo}/merge-upstream
|
||||||
|
await giteaApi(token, 'POST', `/repos/${owner}/${REPO_NAME}/merge-upstream`, {
|
||||||
|
branch: 'main',
|
||||||
|
});
|
||||||
|
} catch (e: any) {
|
||||||
|
// 如果 API 不存在或已同步，忽略
|
||||||
|
if (!e.message.includes('409')) {
|
||||||
|
console.warn('syncFork warning:', e.message);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 列出 skills 目錄下的所有 skill */
|
||||||
|
async function listSkills(token: string, owner: string): Promise<string[]> {
|
||||||
|
const items = await giteaApi(
|
||||||
|
token,
|
||||||
|
'GET',
|
||||||
|
`/repos/${owner}/${REPO_NAME}/contents/skills?ref=main`
|
||||||
|
);
|
||||||
|
return items
|
||||||
|
.filter((item: any) => item.type === 'dir')
|
||||||
|
.map((item: any) => item.name);
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 讀取檔案內容 */
|
||||||
|
async function readFile(
|
||||||
|
token: string,
|
||||||
|
owner: string,
|
||||||
|
filepath: string,
|
||||||
|
ref = 'main'
|
||||||
|
): Promise<GiteaFile> {
|
||||||
|
return giteaApi(
|
||||||
|
token,
|
||||||
|
'GET',
|
||||||
|
`/repos/${owner}/${REPO_NAME}/contents/${filepath}?ref=${ref}`
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 建立分支 */
|
||||||
|
async function createBranch(
|
||||||
|
token: string,
|
||||||
|
owner: string,
|
||||||
|
branchName: string
|
||||||
|
): Promise<void> {
|
||||||
|
await giteaApi(token, 'POST', `/repos/${owner}/${REPO_NAME}/branches`, {
|
||||||
|
new_branch_name: branchName,
|
||||||
|
old_branch_name: 'main',
|
||||||
|
});
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 更新檔案（需要 sha） */
|
||||||
|
async function updateFile(
|
||||||
|
token: string,
|
||||||
|
owner: string,
|
||||||
|
filepath: string,
|
||||||
|
content: string,
|
||||||
|
sha: string,
|
||||||
|
branch: string,
|
||||||
|
message: string
|
||||||
|
): Promise<void> {
|
||||||
|
const b64 = Buffer.from(content, 'utf-8').toString('base64');
|
||||||
|
await giteaApi(
|
||||||
|
token,
|
||||||
|
'PUT',
|
||||||
|
`/repos/${owner}/${REPO_NAME}/contents/${filepath}`,
|
||||||
|
{ content: b64, sha, message, branch }
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 建立新檔案 */
|
||||||
|
async function createFile(
|
||||||
|
token: string,
|
||||||
|
owner: string,
|
||||||
|
filepath: string,
|
||||||
|
content: string,
|
||||||
|
branch: string,
|
||||||
|
message: string
|
||||||
|
): Promise<void> {
|
||||||
|
const b64 = Buffer.from(content, 'utf-8').toString('base64');
|
||||||
|
await giteaApi(
|
||||||
|
token,
|
||||||
|
'POST',
|
||||||
|
`/repos/${owner}/${REPO_NAME}/contents/${filepath}`,
|
||||||
|
{ content: b64, message, branch }
|
||||||
|
);
|
||||||
|
}
|
||||||
|
|
||||||
|
/** 建立 PR（從 fork 到 upstream） */
|
||||||
|
async function createPR(
|
||||||
|
token: string,
|
||||||
|
agentUsername: string,
|
||||||
|
title: string,
|
||||||
|
body: string,
|
||||||
|
branch: string
|
||||||
|
): Promise<{ url: string; number: number }> {
|
||||||
|
const pr = await giteaApi(
|
||||||
|
token,
|
||||||
|
'POST',
|
||||||
|
`/repos/${UPSTREAM_OWNER}/${REPO_NAME}/pulls`,
|
||||||
|
{
|
||||||
|
title,
|
||||||
|
body,
|
||||||
|
head: `${agentUsername}:${branch}`,
|
||||||
|
base: 'main',
|
||||||
|
}
|
||||||
|
);
|
||||||
|
return { url: pr.html_url, number: pr.number };
|
||||||
|
}
|
||||||
|
|
||||||
|
export async function handler(ctx: any) {
|
||||||
|
// 偵測當前 agent
|
||||||
|
const agentId = ctx.env?.OPENCLAW_AGENT_ID || ctx.agentId || 'unknown';
|
||||||
|
const agentConfig = AGENT_MAP[agentId];
|
||||||
|
|
||||||
|
if (!agentConfig) {
|
||||||
|
return {
|
||||||
|
reply: `❌ 無法辨識 agent: ${agentId}\n支援的 agent: ${Object.keys(AGENT_MAP).join(', ')}`,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
const token = ctx.env?.[agentConfig.tokenEnv] || process.env[agentConfig.tokenEnv];
|
||||||
|
if (!token) {
|
||||||
|
return {
|
||||||
|
reply: `❌ 找不到 ${agentConfig.tokenEnv}，請確認 .env 設定。`,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
|
const username = agentConfig.username;
|
||||||
|
|
||||||
|
try {
|
||||||
|
// Step 1: 同步 fork
|
||||||
|
await syncFork(token, username);
|
||||||
|
|
||||||
|
// Step 2: 列出所有 skills
|
||||||
|
const skills = await listSkills(token, username);
|
||||||
|
|
||||||
|
// Step 3: 讀取每個 skill 的內容
|
||||||
|
const skillContents: Record<string, { skillMd: string; handlerTs: string }> = {};
|
||||||
|
|
||||||
|
for (const skill of skills) {
|
||||||
|
try {
|
||||||
|
const skillMdFile = await readFile(token, username, `skills/${skill}/SKILL.md`);
|
||||||
|
const handlerFile = await readFile(token, username, `skills/${skill}/handler.ts`);
|
||||||
|
|
||||||
|
skillContents[skill] = {
|
||||||
|
skillMd: Buffer.from(skillMdFile.content || '', 'base64').toString('utf-8'),
|
||||||
|
handlerTs: Buffer.from(handlerFile.content || '', 'base64').toString('utf-8'),
|
||||||
|
};
|
||||||
|
} catch {
|
||||||
|
// 跳過讀取失敗的 skill
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// 回傳資料供 agent 分析
|
||||||
|
return {
|
||||||
|
reply: `✅ Fork 已同步，共讀取 ${Object.keys(skillContents).length} 個 skills。\n\n請根據你的角色審查以下 skills，選擇一個提出改進 PR。`,
|
||||||
|
data: {
|
||||||
|
agentId,
|
||||||
|
username,
|
||||||
|
skills: skillContents,
|
||||||
|
// 提供 API helper 資訊，讓 agent 知道可以用 exec 呼叫
|
||||||
|
api: {
|
||||||
|
createBranch: 'handler.createBranch(token, owner, branchName)',
|
||||||
|
updateFile: 'handler.updateFile(token, owner, filepath, content, sha, branch, message)',
|
||||||
|
createFile: 'handler.createFile(token, owner, filepath, content, branch, message)',
|
||||||
|
createPR: 'handler.createPR(token, agentUsername, title, body, branch)',
|
||||||
|
},
|
||||||
|
},
|
||||||
|
metadata: { agentId, username, skillCount: Object.keys(skillContents).length },
|
||||||
|
};
|
||||||
|
} catch (err: any) {
|
||||||
|
return {
|
||||||
|
reply: `❌ 執行失敗: ${err.message}`,
|
||||||
|
error: err.message,
|
||||||
|
};
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
// 匯出 helper 供 agent 透過 exec 使用
|
||||||
|
export {
|
||||||
|
syncFork,
|
||||||
|
listSkills,
|
||||||
|
readFile,
|
||||||
|
createBranch,
|
||||||
|
updateFile,
|
||||||
|
createFile,
|
||||||
|
createPR,
|
||||||
|
giteaApi,
|
||||||
|
AGENT_MAP,
|
||||||
|
};
|
||||||
1
skills/summarize
Symbolic link
1
skills/summarize
Symbolic link
@@ -0,0 +1 @@
|
|||||||
|
/home/selig/.openclaw/workspace/skills/summarize
|
||||||
7
skills/tavily-tool/.clawhub/origin.json
Normal file
7
skills/tavily-tool/.clawhub/origin.json
Normal file
@@ -0,0 +1,7 @@
|
|||||||
|
{
|
||||||
|
"version": 1,
|
||||||
|
"registry": "https://clawhub.ai",
|
||||||
|
"slug": "tavily-tool",
|
||||||
|
"installedVersion": "0.1.1",
|
||||||
|
"installedAt": 1773199294594
|
||||||
|
}
|
||||||
46
skills/tavily-tool/SKILL.md
Normal file
46
skills/tavily-tool/SKILL.md
Normal file
@@ -0,0 +1,46 @@
|
|||||||
|
---
|
||||||
|
name: tavily
|
||||||
|
description: Use Tavily web search/discovery to find URLs/sources, do lead research, gather up-to-date links, or produce a cited summary from web results.
|
||||||
|
metadata: {"openclaw":{"requires":{"env":["TAVILY_API_KEY"]},"primaryEnv":"TAVILY_API_KEY"}}
|
||||||
|
---
|
||||||
|
|
||||||
|
# Tavily
|
||||||
|
|
||||||
|
Use the bundled CLI to run Tavily searches from the terminal and collect sources fast.
|
||||||
|
|
||||||
|
## Quick start (CLI)
|
||||||
|
|
||||||
|
The scripts **require** `TAVILY_API_KEY` in the environment (sent as `Authorization: Bearer ...`).
|
||||||
|
|
||||||
|
```bash
|
||||||
|
export TAVILY_API_KEY="..."
|
||||||
|
node skills/tavily/scripts/tavily_search.js --query "best rust http client" --max_results 5
|
||||||
|
```
|
||||||
|
|
||||||
|
- JSON response is printed to **stdout**.
|
||||||
|
- A simple URL list is printed to **stderr** by default.
|
||||||
|
|
||||||
|
## Common patterns
|
||||||
|
|
||||||
|
### Get URLs only
|
||||||
|
|
||||||
|
```bash
|
||||||
|
export TAVILY_API_KEY="..."
|
||||||
|
node skills/tavily/scripts/tavily_search.js --query "OpenTelemetry collector config" --urls-only
|
||||||
|
```
|
||||||
|
|
||||||
|
### Restrict to (or exclude) specific domains
|
||||||
|
|
||||||
|
```bash
|
||||||
|
export TAVILY_API_KEY="..."
|
||||||
|
node skills/tavily/scripts/tavily_search.js \
|
||||||
|
--query "oauth device code flow" \
|
||||||
|
--include_domains oauth.net,datatracker.ietf.org \
|
||||||
|
--exclude_domains medium.com
|
||||||
|
```
|
||||||
|
|
||||||
|
## Notes
|
||||||
|
|
||||||
|
- The bundled CLI supports a subset of Tavily’s request fields (query, max_results, include_domains, exclude_domains).
|
||||||
|
- For API field notes and more examples, read: `references/tavily-api.md`.
|
||||||
|
- Wrapper script (optional): `scripts/tavily_search.sh`.
|
||||||
6
skills/tavily-tool/_meta.json
Normal file
6
skills/tavily-tool/_meta.json
Normal file
@@ -0,0 +1,6 @@
|
|||||||
|
{
|
||||||
|
"ownerId": "kn78x7kg14jggfbz385es5bdrn81ddgw",
|
||||||
|
"slug": "tavily-tool",
|
||||||
|
"version": "0.1.1",
|
||||||
|
"publishedAt": 1772290357545
|
||||||
|
}
|
||||||
55
skills/tavily-tool/references/tavily-api.md
Normal file
55
skills/tavily-tool/references/tavily-api.md
Normal file
@@ -0,0 +1,55 @@
|
|||||||
|
# Tavily API notes (quick reference)
|
||||||
|
|
||||||
|
## Endpoint
|
||||||
|
|
||||||
|
- Search: `POST https://api.tavily.com/search`
|
||||||
|
|
||||||
|
## Auth
|
||||||
|
|
||||||
|
- Send the API key via HTTP header: `Authorization: Bearer <TAVILY_API_KEY>`.
|
||||||
|
- This skill’s scripts read the key from **env var only**: `TAVILY_API_KEY`.
|
||||||
|
|
||||||
|
## Common request fields
|
||||||
|
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"query": "...",
|
||||||
|
"max_results": 5,
|
||||||
|
"include_domains": ["example.com"],
|
||||||
|
"exclude_domains": ["spam.com"]
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
(Additional Tavily options exist; this skill’s CLI supports only a common subset for discovery use-cases.)
|
||||||
|
|
||||||
|
## Script usage
|
||||||
|
|
||||||
|
### JSON output (stdout) + URL list (stderr)
|
||||||
|
|
||||||
|
```bash
|
||||||
|
export TAVILY_API_KEY="..."
|
||||||
|
node skills/tavily/scripts/tavily_search.js --query "best open source vector database" --max_results 5
|
||||||
|
```
|
||||||
|
|
||||||
|
### URLs only
|
||||||
|
|
||||||
|
```bash
|
||||||
|
export TAVILY_API_KEY="..."
|
||||||
|
node skills/tavily/scripts/tavily_search.js --query "SvelteKit tutorial" --urls-only
|
||||||
|
```
|
||||||
|
|
||||||
|
### Include / exclude domains
|
||||||
|
|
||||||
|
```bash
|
||||||
|
export TAVILY_API_KEY="..."
|
||||||
|
node skills/tavily/scripts/tavily_search.js \
|
||||||
|
--query "websocket load testing" \
|
||||||
|
--include_domains k6.io,github.com \
|
||||||
|
--exclude_domains medium.com
|
||||||
|
```
|
||||||
|
|
||||||
|
## Notes
|
||||||
|
|
||||||
|
- Exit code `2` indicates missing required args or missing `TAVILY_API_KEY`.
|
||||||
|
- Exit code `3` indicates network/HTTP failure.
|
||||||
|
- Exit code `4` indicates a non-JSON response.
|
||||||
161
skills/tavily-tool/scripts/tavily_search.js
Normal file
161
skills/tavily-tool/scripts/tavily_search.js
Normal file
@@ -0,0 +1,161 @@
|
|||||||
|
#!/usr/bin/env node
|
||||||
|
/**
|
||||||
|
* Tavily Search CLI
|
||||||
|
*
|
||||||
|
* - Reads TAVILY_API_KEY from env only.
|
||||||
|
* - Prints full JSON response to stdout.
|
||||||
|
* - Prints a simple list of URLs to stderr by default (can be disabled).
|
||||||
|
*/
|
||||||
|
|
||||||
|
const TAVILY_ENDPOINT = 'https://api.tavily.com/search';
|
||||||
|
|
||||||
|
function usage(msg) {
|
||||||
|
if (msg) console.error(`Error: ${msg}\n`);
|
||||||
|
console.error(`Usage:
|
||||||
|
tavily_search.js --query "..." [--max_results 5] [--include_domains a.com,b.com] [--exclude_domains x.com,y.com]
|
||||||
|
|
||||||
|
Options:
|
||||||
|
--query, -q Search query (required)
|
||||||
|
--max_results, -n Max results (default: 5; clamped to 0..20)
|
||||||
|
--include_domains Comma-separated domains to include
|
||||||
|
--exclude_domains Comma-separated domains to exclude
|
||||||
|
--urls-stderr Print URL list to stderr (default: true)
|
||||||
|
--no-urls-stderr Disable URL list to stderr
|
||||||
|
--urls-only Print URLs (one per line) to stdout instead of JSON
|
||||||
|
--help, -h Show help
|
||||||
|
|
||||||
|
Env:
|
||||||
|
TAVILY_API_KEY (required) Tavily API key
|
||||||
|
|
||||||
|
Exit codes:
|
||||||
|
0 success
|
||||||
|
2 usage / missing required inputs
|
||||||
|
3 network / HTTP error
|
||||||
|
4 invalid JSON response
|
||||||
|
`);
|
||||||
|
}
|
||||||
|
|
||||||
|
function parseArgs(argv) {
|
||||||
|
const out = {
|
||||||
|
query: null,
|
||||||
|
max_results: 5,
|
||||||
|
include_domains: null,
|
||||||
|
exclude_domains: null,
|
||||||
|
urls_stderr: true,
|
||||||
|
urls_only: false,
|
||||||
|
help: false,
|
||||||
|
};
|
||||||
|
|
||||||
|
for (let i = 0; i < argv.length; i++) {
|
||||||
|
const a = argv[i];
|
||||||
|
if (a === '--help' || a === '-h') out.help = true;
|
||||||
|
else if (a === '--query' || a === '-q') out.query = argv[++i];
|
||||||
|
else if (a === '--max_results' || a === '-n') out.max_results = Number(argv[++i]);
|
||||||
|
else if (a === '--include_domains') out.include_domains = argv[++i];
|
||||||
|
else if (a === '--exclude_domains') out.exclude_domains = argv[++i];
|
||||||
|
else if (a === '--urls-stderr') out.urls_stderr = true;
|
||||||
|
else if (a === '--no-urls-stderr') out.urls_stderr = false;
|
||||||
|
else if (a === '--urls-only') out.urls_only = true;
|
||||||
|
else return { error: `Unknown arg: ${a}` };
|
||||||
|
}
|
||||||
|
|
||||||
|
if (Number.isNaN(out.max_results) || !Number.isFinite(out.max_results)) {
|
||||||
|
return { error: `--max_results must be a number` };
|
||||||
|
}
|
||||||
|
// Tavily allows 0..20; clamp to stay in range.
|
||||||
|
out.max_results = Math.max(0, Math.min(20, Math.trunc(out.max_results)));
|
||||||
|
|
||||||
|
const csvToArray = (s) => {
|
||||||
|
if (!s) return null;
|
||||||
|
const arr = s.split(',').map(x => x.trim()).filter(Boolean);
|
||||||
|
return arr.length ? arr : null;
|
||||||
|
};
|
||||||
|
|
||||||
|
out.include_domains = csvToArray(out.include_domains);
|
||||||
|
out.exclude_domains = csvToArray(out.exclude_domains);
|
||||||
|
|
||||||
|
return out;
|
||||||
|
}
|
||||||
|
|
||||||
|
async function main() {
|
||||||
|
const args = parseArgs(process.argv.slice(2));
|
||||||
|
if (args.error) {
|
||||||
|
usage(args.error);
|
||||||
|
process.exit(2);
|
||||||
|
}
|
||||||
|
if (args.help) {
|
||||||
|
usage();
|
||||||
|
process.exit(0);
|
||||||
|
}
|
||||||
|
|
||||||
|
const apiKey = process.env.TAVILY_API_KEY;
|
||||||
|
if (!apiKey) {
|
||||||
|
usage('TAVILY_API_KEY env var is required');
|
||||||
|
process.exit(2);
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!args.query) {
|
||||||
|
usage('--query is required');
|
||||||
|
process.exit(2);
|
||||||
|
}
|
||||||
|
|
||||||
|
const payload = {
|
||||||
|
query: args.query,
|
||||||
|
max_results: args.max_results,
|
||||||
|
};
|
||||||
|
if (args.include_domains) payload.include_domains = args.include_domains;
|
||||||
|
if (args.exclude_domains) payload.exclude_domains = args.exclude_domains;
|
||||||
|
|
||||||
|
let res;
|
||||||
|
try {
|
||||||
|
res = await fetch(TAVILY_ENDPOINT, {
|
||||||
|
method: 'POST',
|
||||||
|
headers: {
|
||||||
|
'Content-Type': 'application/json',
|
||||||
|
'Authorization': `Bearer ${apiKey}`,
|
||||||
|
},
|
||||||
|
body: JSON.stringify(payload),
|
||||||
|
});
|
||||||
|
} catch (e) {
|
||||||
|
console.error(`Network error calling Tavily: ${e?.message || String(e)}`);
|
||||||
|
process.exit(3);
|
||||||
|
}
|
||||||
|
|
||||||
|
if (!res.ok) {
|
||||||
|
let bodyText = '';
|
||||||
|
try { bodyText = await res.text(); } catch {}
|
||||||
|
console.error(`Tavily HTTP error: ${res.status} ${res.statusText}`);
|
||||||
|
if (bodyText) console.error(bodyText);
|
||||||
|
process.exit(3);
|
||||||
|
}
|
||||||
|
|
||||||
|
let data;
|
||||||
|
try {
|
||||||
|
data = await res.json();
|
||||||
|
} catch (e) {
|
||||||
|
console.error(`Invalid JSON response from Tavily: ${e?.message || String(e)}`);
|
||||||
|
process.exit(4);
|
||||||
|
}
|
||||||
|
|
||||||
|
const urls = Array.isArray(data?.results)
|
||||||
|
? data.results.map(r => r?.url).filter(Boolean)
|
||||||
|
: [];
|
||||||
|
|
||||||
|
if (args.urls_only) {
|
||||||
|
for (const u of urls) process.stdout.write(`${u}\n`);
|
||||||
|
process.exit(0);
|
||||||
|
}
|
||||||
|
|
||||||
|
process.stdout.write(JSON.stringify(data, null, 2));
|
||||||
|
process.stdout.write('\n');
|
||||||
|
|
||||||
|
if (args.urls_stderr && urls.length) {
|
||||||
|
console.error('\nURLs:');
|
||||||
|
for (const u of urls) console.error(u);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
main().catch((e) => {
|
||||||
|
console.error(`Unexpected error: ${e?.stack || e?.message || String(e)}`);
|
||||||
|
process.exit(1);
|
||||||
|
});
|
||||||
9
skills/tavily-tool/scripts/tavily_search.sh
Normal file
9
skills/tavily-tool/scripts/tavily_search.sh
Normal file
@@ -0,0 +1,9 @@
|
|||||||
|
#!/usr/bin/env bash
|
||||||
|
set -euo pipefail
|
||||||
|
|
||||||
|
# Wrapper to run the Node Tavily search CLI.
|
||||||
|
# Usage:
|
||||||
|
# TAVILY_API_KEY=... ./tavily_search.sh --query "..." --max_results 5
|
||||||
|
|
||||||
|
DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
|
||||||
|
exec node "$DIR/tavily_search.js" "$@"
|
||||||
@@ -8,7 +8,7 @@
|
|||||||
* - curl CLI
|
* - curl CLI
|
||||||
*/
|
*/
|
||||||
|
|
||||||
import { execSync } from 'child_process';
|
import { execSync, spawnSync } from 'child_process';
|
||||||
import { readFileSync, existsSync, unlinkSync } from 'fs';
|
import { readFileSync, existsSync, unlinkSync } from 'fs';
|
||||||
|
|
||||||
const LUXTTS_BASE = 'http://localhost:7860';
|
const LUXTTS_BASE = 'http://localhost:7860';
|
||||||
@@ -113,19 +113,28 @@ function generateSpeech(text: string, params: TtsParams): string | null {
|
|||||||
const outPath = `/tmp/tts_output_${timestamp}.wav`;
|
const outPath = `/tmp/tts_output_${timestamp}.wav`;
|
||||||
|
|
||||||
try {
|
try {
|
||||||
const httpCode = execSync(
|
const args = [
|
||||||
`curl -s -o ${outPath} -w "%{http_code}" ` +
|
'-s',
|
||||||
`-b ${COOKIE_JAR} ` +
|
'-o', outPath,
|
||||||
`-X POST ${LUXTTS_BASE}/luxtts/api/tts ` +
|
'-w', '%{http_code}',
|
||||||
`-F "ref_audio=@${REF_AUDIO}" ` +
|
'-b', COOKIE_JAR,
|
||||||
`-F "text=${text.replace(/"/g, '\\"')}" ` +
|
'-X', 'POST',
|
||||||
`-F "num_steps=${params.numSteps}" ` +
|
`${LUXTTS_BASE}/luxtts/api/tts`,
|
||||||
`-F "t_shift=${params.tShift}" ` +
|
'-F', `ref_audio=@${REF_AUDIO}`,
|
||||||
`-F "speed=${params.speed}"`,
|
'-F', `text=${text}`,
|
||||||
{ timeout: 120000 } // 2 min timeout for CPU synthesis
|
'-F', `num_steps=${params.numSteps}`,
|
||||||
).toString().trim();
|
'-F', `t_shift=${params.tShift}`,
|
||||||
|
'-F', `speed=${params.speed}`,
|
||||||
|
];
|
||||||
|
|
||||||
if (httpCode === '200' && existsSync(outPath)) {
|
const result = spawnSync('curl', args, {
|
||||||
|
timeout: 120000, // 2 min timeout for CPU synthesis
|
||||||
|
encoding: 'utf-8',
|
||||||
|
});
|
||||||
|
|
||||||
|
const httpCode = (result.stdout || '').trim();
|
||||||
|
|
||||||
|
if (result.status === 0 && httpCode === '200' && existsSync(outPath)) {
|
||||||
return outPath;
|
return outPath;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|||||||
Reference in New Issue
Block a user