Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/sbusso/claudeclawnpx agentmods add skills/sbusso/claudeclaw/add-ollama-toolWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sbusso/claudeclaw/add-ollama-tool)<a href="https://agentmods.dev/skills/sbusso/claudeclaw/add-ollama-tool"><img src="https://agentmods.dev/badge/skills/sbusso/claudeclaw/add-ollama-tool/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sbusso/claudeclaw/add-ollama-tool"><img src="https://agentmods.dev/badge/skills/sbusso/claudeclaw/add-ollama-tool.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 150 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
- low Tool Misuse · line 150 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.01194 |
| Opus 5 | $0.00017 | $0.00597 |
| Sonnet 5 | $0.00007 | $0.00239 |
| Haiku 4.5 | $0.00003 | $0.00119 |
Grade A, and why
add-ollama-tool scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
2. Check Docker can reach the host: `docker run --rm curlimages/curl curl -s http://host.docker.internal:11434/api/tags` Copies of this mod
2 near-identical copies found in the catalogue:
- add-ollama-tool — 89% identical, 28 lines differ
- add-ollama-tool — 84% identical, 46 lines differ
How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 modelsollama_generate— sends a prompt to a specified model and returns the response
Phase 1: Pre-flight
Check if already applied
Check if agent/runner/src/ollama-mcp-stdio.ts exists. If it does, skip to Phase 3 (Configure).
Check prerequisites
Verify Ollama is installed and running on the host:
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:
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
Ensure upstream remote
git remote -v
If upstream is missing, add it:
git remote add upstream https://github.com/sbusso/claudeclaw.git
Merge the skill branch
git fetch upstream skill/ollama-tool
git merge upstream/skill/ollama-tool
This merges in:
agent/runner/src/ollama-mcp-stdio.ts(Ollama MCP server)scripts/ollama-watch.sh(macOS notification watcher)- Ollama MCP config in
agent/runner/src/index.ts(allowedTools + mcpServers) [OLLAMA]log surfacing insrc/orchestrator/container-runner.tsOLLAMA_HOSTin.env.example
If the merge reports conflicts, resolve them by reading the conflicted files and understanding the intent of both sides.
Copy to per-group agent-runner
Existing groups have a cached copy of the agent-runner source. Copy the new files:
for dir in data/sessions/*/agent-runner-src; do
cp agent/runner/src/ollama-mcp-stdio.ts "$dir/"
cp agent/runner/src/index.ts "$dir/"
done
Validate code changes
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 156 lines · 34 tokens per session scan A 7241bbf3a227
add-ollama-tool is a skill published in the GitHub repository sbusso/claudeclaw (192 stars, last pushed 28d ago), licensed MIT. It adds 34 tokens to every session and 1,194 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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