Borrowing it
Nothing to install: this file belongs to refactornator/nanoflash. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/refactornator/nanoflash/main/.claude/skills/add-ollama-tool/SKILL.mdgit clone --depth 1 https://github.com/refactornator/nanoflashWrote 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/refactornator/nanoflash/add-ollama-tool)<a href="https://agentmods.dev/skills/refactornator/nanoflash/add-ollama-tool"><img src="https://agentmods.dev/badge/skills/refactornator/nanoflash/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/refactornator/nanoflash/add-ollama-tool"><img src="https://agentmods.dev/badge/skills/refactornator/nanoflash/add-ollama-tool.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00028 | $0.01538 |
| Opus 5 | $0.00014 | $0.00769 |
| Sonnet 5 | $0.00006 | $0.00308 |
| Haiku 4.5 | $0.00003 | $0.00154 |
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` This is a copy
92% identical to add-ollama-tool — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 194 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, and can optionally manage the model library directly.
Core tools (always available):
ollama_list_models— list installed Ollama models with name, size, and familyollama_generate— send a prompt to a specified model and return the response
Management tools (opt-in via OLLAMA_ADMIN_TOOLS=true):
ollama_pull_model— pull (download) a model from the Ollama registryollama_delete_model— delete a locally installed model to free disk spaceollama_show_model— show model details: modelfile, parameters, and architecture infoollama_list_running— list models currently loaded in memory with memory usage and processor type
Phase 1: Pre-flight
Check if already applied
Check if container/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/qwibitai/nanoclaw.git
Merge the skill branch
git fetch upstream skill/ollama-tool
git merge upstream/skill/ollama-tool
This merges in:
container/agent-runner/src/ollama-mcp-stdio.ts(Ollama MCP server)scripts/ollama-watch.sh(macOS notification watcher)- Ollama MCP config in
container/agent-runner/src/index.ts(allowedTools + mcpServers) [OLLAMA]log surfacing insrc/container-runner.tsOLLAMA_HOSTin.env.example
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 · 194 lines · 28 tokens per session scan A a8f474676557
add-ollama-tool is a skill published in the GitHub repository refactornator/nanoflash (5 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 1,538 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 92% identical to add-ollama-tool, differing in 11 lines, and is treated as a copy.
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