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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> ## Documentation Index
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> Fetch the complete documentation index at: https://docs.openclaw.ai/llms.txt
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> Use this file to discover all available pages before exploring further.
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# Local Models
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# Local models
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Local is doable, but OpenClaw expects large context + strong defenses against prompt injection. Small cards truncate context and leak safety. Aim high: **≥2 maxed-out Mac Studios or equivalent GPU rig (\~\$30k+)**. A single **24 GB** GPU works only for lighter prompts with higher latency. Use the **largest / full-size model variant you can run**; aggressively quantized or “small” checkpoints raise prompt-injection risk (see [Security](/gateway/security)).
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## Recommended: LM Studio + MiniMax M2.1 (Responses API, full-size)
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Best current local stack. Load MiniMax M2.1 in LM Studio, enable the local server (default `http://127.0.0.1:1234`), and use Responses API to keep reasoning separate from final text.
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```json5 theme={null}
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{
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agents: {
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defaults: {
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model: { primary: "lmstudio/minimax-m2.1-gs32" },
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models: {
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"anthropic/claude-opus-4-6": { alias: "Opus" },
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"lmstudio/minimax-m2.1-gs32": { alias: "Minimax" },
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},
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},
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},
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models: {
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mode: "merge",
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providers: {
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lmstudio: {
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baseUrl: "http://127.0.0.1:1234/v1",
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apiKey: "lmstudio",
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api: "openai-responses",
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models: [
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{
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id: "minimax-m2.1-gs32",
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name: "MiniMax M2.1 GS32",
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reasoning: false,
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input: ["text"],
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: 196608,
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maxTokens: 8192,
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},
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],
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},
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},
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},
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}
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```
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**Setup checklist**
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* Install LM Studio: [https://lmstudio.ai](https://lmstudio.ai)
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* In LM Studio, download the **largest MiniMax M2.1 build available** (avoid “small”/heavily quantized variants), start the server, confirm `http://127.0.0.1:1234/v1/models` lists it.
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* Keep the model loaded; cold-load adds startup latency.
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* Adjust `contextWindow`/`maxTokens` if your LM Studio build differs.
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* For WhatsApp, stick to Responses API so only final text is sent.
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Keep hosted models configured even when running local; use `models.mode: "merge"` so fallbacks stay available.
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### Hybrid config: hosted primary, local fallback
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```json5 theme={null}
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{
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agents: {
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defaults: {
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model: {
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primary: "anthropic/claude-sonnet-4-5",
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fallbacks: ["lmstudio/minimax-m2.1-gs32", "anthropic/claude-opus-4-6"],
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},
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models: {
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"anthropic/claude-sonnet-4-5": { alias: "Sonnet" },
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"lmstudio/minimax-m2.1-gs32": { alias: "MiniMax Local" },
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"anthropic/claude-opus-4-6": { alias: "Opus" },
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},
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},
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},
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models: {
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mode: "merge",
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providers: {
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lmstudio: {
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baseUrl: "http://127.0.0.1:1234/v1",
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apiKey: "lmstudio",
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api: "openai-responses",
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models: [
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{
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id: "minimax-m2.1-gs32",
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name: "MiniMax M2.1 GS32",
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reasoning: false,
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input: ["text"],
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: 196608,
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maxTokens: 8192,
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},
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],
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},
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},
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},
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}
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```
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### Local-first with hosted safety net
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Swap the primary and fallback order; keep the same providers block and `models.mode: "merge"` so you can fall back to Sonnet or Opus when the local box is down.
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### Regional hosting / data routing
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* Hosted MiniMax/Kimi/GLM variants also exist on OpenRouter with region-pinned endpoints (e.g., US-hosted). Pick the regional variant there to keep traffic in your chosen jurisdiction while still using `models.mode: "merge"` for Anthropic/OpenAI fallbacks.
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* Local-only remains the strongest privacy path; hosted regional routing is the middle ground when you need provider features but want control over data flow.
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## Other OpenAI-compatible local proxies
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vLLM, LiteLLM, OAI-proxy, or custom gateways work if they expose an OpenAI-style `/v1` endpoint. Replace the provider block above with your endpoint and model ID:
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```json5 theme={null}
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{
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models: {
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mode: "merge",
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providers: {
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local: {
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baseUrl: "http://127.0.0.1:8000/v1",
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apiKey: "sk-local",
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api: "openai-responses",
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models: [
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{
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id: "my-local-model",
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name: "Local Model",
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reasoning: false,
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input: ["text"],
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: 120000,
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maxTokens: 8192,
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},
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],
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},
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},
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},
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}
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```
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Keep `models.mode: "merge"` so hosted models stay available as fallbacks.
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## Troubleshooting
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* Gateway can reach the proxy? `curl http://127.0.0.1:1234/v1/models`.
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* LM Studio model unloaded? Reload; cold start is a common “hanging” cause.
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* Context errors? Lower `contextWindow` or raise your server limit.
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* Safety: local models skip provider-side filters; keep agents narrow and compaction on to limit prompt injection blast radius.
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