auto: 2026-02-20 - update email processor, add ollama-local skill

skills/ollama-local/references/models.md

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+# Model Guide
+
+This reference covers common Ollama models and selection guidance.
+
+## Popular Models
+
+### Chat/General Models
+
+| Model | Params | Best For | Notes |
+|-------|--------|----------|-------|
+| `qwen3:4b` | 4B | Fast tasks, quick answers | Thinking-enabled, very fast |
+| `llama3.1:8b` | 8B | General chat, reasoning | Good all-rounder |
+| `gemma3:12b` | 12.2B | Creative, design tasks | Google model, good quality |
+| `phi4-reasoning:latest` | 14.7B | Complex reasoning | Thinking-enabled |
+| `mistral-small3.1:latest` | 24B | Technical tasks | May need CPU offload |
+| `deepseek-r1:8b` | 8.2B | Deep reasoning | Thinking-enabled, chain-of-thought |
+
+### Coding Models
+
+| Model | Params | Best For | Notes |
+|-------|--------|----------|-------|
+| `qwen2.5-coder:7b` | 7.6B | Code generation, review | Best local coding model |
+| `codellama:7b` | 7B | Code completion | Meta's code model |
+| `deepseek-coder:6.7b` | 6.7B | Code tasks | Good alternative |
+
+### Embedding Models
+
+| Model | Params | Dimensions | Notes |
+|-------|--------|------------|-------|
+| `bge-m3:latest` | 567M | 1024 | Multilingual, good quality |
+| `nomic-embed-text` | 137M | 768 | Fast, English-focused |
+| `mxbai-embed-large` | 335M | 1024 | High quality embeddings |
+
+## Model Selection Guide
+
+### By Task Type
+
+- **Quick questions**: `qwen3:4b` (fastest)
+- **General chat**: `llama3.1:8b`
+- **Coding**: `qwen2.5-coder:7b`
+- **Complex reasoning**: `phi4-reasoning` or `deepseek-r1:8b`
+- **Creative/design**: `gemma3:12b`
+- **Embeddings**: `bge-m3:latest`
+
+### By Speed vs Quality
+
+```
+Fastest ←──────────────────────────────→ Best Quality
+qwen3:4b → llama3.1:8b → gemma3:12b → mistral-small3.1
+```
+
+### Tool Use Support
+
+Models with good tool/function calling support:
+- ✅ `qwen2.5-coder:7b` - Excellent
+- ✅ `qwen3:4b` - Good
+- ✅ `llama3.1:8b` - Basic
+- ✅ `mistral` models - Good
+- ⚠️ Others - May not support tools natively
+
+## OpenClaw Integration
+
+To use Ollama models in OpenClaw sub-agents, use these model paths:
+
+```
+ollama/qwen3:4b
+ollama/llama3.1:8b
+ollama/qwen2.5-coder:7b
+ollama/gemma3:12b
+ollama/mistral-small3.1:latest
+ollama/phi4-reasoning:latest
+ollama/deepseek-r1:8b
+```
+
+### Auth Profile Required
+
+OpenClaw requires an auth profile even for Ollama (no actual auth needed). Add to `auth-profiles.json`:
+
+```json
+"ollama:default": {
+  "type": "api_key",
+  "provider": "ollama",
+  "key": "ollama"
+}
+```
+
+## Hardware Considerations
+
+- **8GB VRAM**: Can run models up to ~13B comfortably
+- **16GB VRAM**: Can run most models including 24B+
+- **CPU offload**: Ollama automatically offloads to CPU/RAM for larger models
+- **Larger models** may be slower due to partial CPU inference
+
+## Installing Models
+
+```bash
+# Pull a model
+ollama pull llama3.1:8b
+
+# Or via the skill script
+python3 scripts/ollama.py pull llama3.1:8b
+
+# List installed models
+python3 scripts/ollama.py list
+```