feat: add /add-ollama skill for local model inference (#712)

* feat: add /add-ollama skill for local model inference

Adds a skill that integrates Ollama as an MCP server, allowing the
container agent to offload tasks to local models (summarization,
translation, general queries) while keeping Claude as orchestrator.

Skill contents:
- ollama-mcp-stdio.ts: stdio MCP server with ollama_list_models and
  ollama_generate tools
- ollama-watch.sh: macOS notification watcher for Ollama activity
- Modifications to index.ts (MCP config) and container-runner.ts
  (log surfacing)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* chore: rename skill from /add-ollama to /add-ollama-tool

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: gavrielc <gabicohen22@yahoo.com>

.claude/skills/add-ollama-tool/SKILL.md

@@ -0,0 +1,152 @@
+---
+name: add-ollama-tool
+description: Add Ollama MCP server so the container agent can call local models for cheaper/faster tasks like summarization, translation, or general queries.
+---
+
+# Add Ollama Integration
+
+This skill adds a stdio-based MCP server that exposes local Ollama models as tools for the container agent. Claude remains the orchestrator but can offload work to local models.
+
+Tools added:
+- `ollama_list_models` — lists installed Ollama models
+- `ollama_generate` — sends a prompt to a specified model and returns the response
+
+## Phase 1: Pre-flight
+
+### Check if already applied
+
+Read `.nanoclaw/state.yaml`. If `ollama` is in `applied_skills`, skip to Phase 3 (Configure). The code changes are already in place.
+
+### Check prerequisites
+
+Verify Ollama is installed and running on the host:
+
+```bash
+ollama list
+```
+
+If Ollama is not installed, direct the user to https://ollama.com/download.
+
+If no models are installed, suggest pulling one:
+
+> You need at least one model. I recommend:
+>
+> ```bash
+> ollama pull gemma3:1b    # Small, fast (1GB)
+> ollama pull llama3.2     # Good general purpose (2GB)
+> ollama pull qwen3-coder:30b  # Best for code tasks (18GB)
+> ```
+
+## Phase 2: Apply Code Changes
+
+Run the skills engine to apply this skill's code package.
+
+### Initialize skills system (if needed)
+
+If `.nanoclaw/` directory doesn't exist yet:
+
+```bash
+npx tsx scripts/apply-skill.ts --init
+```
+
+### Apply the skill
+
+```bash
+npx tsx scripts/apply-skill.ts .claude/skills/add-ollama-tool
+```
+
+This deterministically:
+- Adds `container/agent-runner/src/ollama-mcp-stdio.ts` (Ollama MCP server)
+- Adds `scripts/ollama-watch.sh` (macOS notification watcher)
+- Three-way merges Ollama MCP config into `container/agent-runner/src/index.ts` (allowedTools + mcpServers)
+- Three-way merges `[OLLAMA]` log surfacing into `src/container-runner.ts`
+- Records the application in `.nanoclaw/state.yaml`
+
+If the apply reports merge conflicts, read the intent files:
+- `modify/container/agent-runner/src/index.ts.intent.md` — what changed and invariants
+- `modify/src/container-runner.ts.intent.md` — what changed and invariants
+
+### Copy to per-group agent-runner
+
+Existing groups have a cached copy of the agent-runner source. Copy the new files:
+
+```bash
+for dir in data/sessions/*/agent-runner-src; do
+  cp container/agent-runner/src/ollama-mcp-stdio.ts "$dir/"
+  cp container/agent-runner/src/index.ts "$dir/"
+done
+```
+
+### Validate code changes
+
+```bash
+npm run build
+./container/build.sh
+```
+
+Build must be clean before proceeding.
+
+## Phase 3: Configure
+
+### Set Ollama host (optional)
+
+By default, the MCP server connects to `http://host.docker.internal:11434` (Docker Desktop) with a fallback to `localhost`. To use a custom Ollama host, add to `.env`:
+
+```bash
+OLLAMA_HOST=http://your-ollama-host:11434
+```
+
+### Restart the service
+
+```bash
+launchctl kickstart -k gui/$(id -u)/com.nanoclaw  # macOS
+# Linux: systemctl --user restart nanoclaw
+```
+
+## Phase 4: Verify
+
+### Test via WhatsApp
+
+Tell the user:
+
+> Send a message like: "use ollama to tell me the capital of France"
+>
+> The agent should use `ollama_list_models` to find available models, then `ollama_generate` to get a response.
+
+### Monitor activity (optional)
+
+Run the watcher script for macOS notifications when Ollama is used:
+
+```bash
+./scripts/ollama-watch.sh
+```
+
+### Check logs if needed
+
+```bash
+tail -f logs/nanoclaw.log | grep -i ollama
+```
+
+Look for:
+- `Agent output: ... Ollama ...` — agent used Ollama successfully
+- `[OLLAMA] >>> Generating` — generation started (if log surfacing works)
+- `[OLLAMA] <<< Done` — generation completed
+
+## Troubleshooting
+
+### Agent says "Ollama is not installed"
+
+The agent is trying to run `ollama` CLI inside the container instead of using the MCP tools. This means:
+1. The MCP server wasn't registered — check `container/agent-runner/src/index.ts` has the `ollama` entry in `mcpServers`
+2. The per-group source wasn't updated — re-copy files (see Phase 2)
+3. The container wasn't rebuilt — run `./container/build.sh`
+
+### "Failed to connect to Ollama"
+
+1. Verify Ollama is running: `ollama list`
+2. Check Docker can reach the host: `docker run --rm curlimages/curl curl -s http://host.docker.internal:11434/api/tags`
+3. If using a custom host, check `OLLAMA_HOST` in `.env`
+
+### Agent doesn't use Ollama tools
+
+The agent may not know about the tools. Try being explicit: "use the ollama_generate tool with gemma3:1b to answer: ..."