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feat: skills as branches, channels as forks

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Replace the custom skills engine with standard git operations.
Feature skills are now git branches (on upstream or channel forks)
applied via `git merge`. Channels are separate fork repos.

- Remove skills-engine/ (6,300+ lines), apply/uninstall/rebase scripts
- Remove old skill format (add/, modify/, manifest.yaml) from all skills
- Remove old CI (skill-drift.yml, skill-pr.yml)
- Add merge-forward CI for upstream skill branches
- Add fork notification (repository_dispatch to channel forks)
- Add marketplace config (.claude/settings.json)
- Add /update-skills operational skill
- Update /setup and /customize for marketplace plugin install
- Add docs/skills-as-branches.md architecture doc

Channel forks created: nanoclaw-whatsapp (with 5 skill branches),
nanoclaw-telegram, nanoclaw-discord, nanoclaw-slack, nanoclaw-gmail.

Upstream retains: skill/ollama-tool, skill/apple-container, skill/compact.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
gavrielc
2026-03-10 00:18:25 +02:00
parent e7852a45a5
commit 5118239cea
182 changed files with 1065 additions and 36205 deletions
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.claude/skills/add-ollama-tool/SKILL.md
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---
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: ..."