Initial commit: OpenClaw Skill Collection

6 custom skills (assign-task, dispatch-webhook, daily-briefing,
task-capture, qmd-brain, tts-voice) with technical documentation.
Compatible with Claude Code, OpenClaw, Codex CLI, and OpenCode.
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2026-03-13 10:58:30 +08:00
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# Memory
OpenClaw's memory system uses plain Markdown in the agent workspace as the foundational approach. Files serve as the authoritative source rather than RAM-based storage.
## Memory File Structure
The system organizes information across two layers:
### Daily logs (`memory/YYYY-MM-DD.md`)
Append-only daily entries, with today's and yesterday's files loaded at session start.
### Long-term memory (`MEMORY.md`)
Curated persistent information, loaded only in private sessions.
## Writing to Memory
Recommended storage patterns:
- **Decisions, preferences, and durable facts** go to `MEMORY.md`
- **Ephemeral notes and contextual information** in daily logs
- **Explicit requests to remember something** should be written immediately
## Automatic Memory Management
When sessions approach token limits, OpenClaw triggers a silent agentic turn prompting memory consolidation before context compaction occurs.
This flush mechanism can be configured via `agents.defaults.compaction.memoryFlush` settings:
```json5
{
agents: {
defaults: {
compaction: {
memoryFlush: {
enabled: true,
softThresholdTokens: 4000,
prompt: "...",
systemPrompt: "..."
}
}
}
}
}
```
## Search Capabilities
The system supports vector-based semantic search across memory files, with configurable backends including:
| Backend | Description |
|---------|-------------|
| Built-in SQLite | Optional vector acceleration |
| QMD sidecar | Local-first search combining BM25 + vectors + reranking |
| Hybrid search | Merges both keyword and semantic signals |
### Tools
- `memory_search` - Semantic queries across memory files
- `memory_get` - Direct file retrieval