Borrowing it
Nothing to install: this file belongs to taslim/nanoclaw-gws-ea. 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/taslim/nanoclaw-gws-ea/main/.claude/skills/add-atomic-chat-tool/SKILL.mdgit clone --depth 1 https://github.com/taslim/nanoclaw-gws-eaWrote 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/taslim/nanoclaw-gws-ea/add-atomic-chat-tool)<a href="https://agentmods.dev/skills/taslim/nanoclaw-gws-ea/add-atomic-chat-tool"><img src="https://agentmods.dev/badge/skills/taslim/nanoclaw-gws-ea/add-atomic-chat-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/taslim/nanoclaw-gws-ea/add-atomic-chat-tool"><img src="https://agentmods.dev/badge/skills/taslim/nanoclaw-gws-ea/add-atomic-chat-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 | $0.00033 | $0.02215 |
| Opus 5 | $0.00016 | $0.01107 |
| Sonnet 5 | $0.00007 | $0.00443 |
| Haiku 4.5 | $0.00003 | $0.00221 |
Grade A, and why
add-atomic-chat-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 12d 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.
curl -s http://127.0.0.1:1337/v1/models | head Copies of this mod
1 near-identical copy found in the catalogue:
- add-atomic-chat-tool — 98% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add Atomic Chat Integration
This skill adds a stdio-based MCP server that exposes models running in the local Atomic Chat desktop app as tools for the container agent. Claude remains the orchestrator but can offload work to local models served by Atomic Chat on http://127.0.0.1:1337/v1 (OpenAI-compatible).
Tools exposed:
atomic_chat_list_models— list models currently available in Atomic Chat (GET /v1/models)atomic_chat_generate— send a prompt to a specified model and return the response (POST /v1/chat/completions)
Model management (download, delete) is done through the Atomic Chat desktop UI — the app is a fork of Jan and manages its own model library.
The skill ships the MCP server source in this folder and copies it into the agent-runner tree at install time, then wires it up with small edits to index.ts, providers/claude.ts, and container-runner.ts. No branch merge — all edits are additive and idempotent.
Phase 1: Pre-flight
Check if already applied
Check if container/agent-runner/src/atomic-chat-mcp-stdio.ts exists. If it does, skip to Phase 3 (Configure).
Check prerequisites
Verify Atomic Chat is installed and its local API server is running. On the host:
curl -s http://127.0.0.1:1337/v1/models | head
If the request fails:
- Install Atomic Chat from the latest release (macOS only for now —
atomic-chat.dmg). - Open the app.
- Open Settings → Local API Server and make sure it's enabled on port
1337. - Go to the Hub (or Models) tab and download at least one model (e.g. Llama 3.2 3B, Qwen 2.5 Coder 7B).
- Load the model once by sending any message in Atomic Chat's UI to warm it up.
Phase 2: Apply Code Changes
Copy the MCP server source
cp .claude/skills/add-atomic-chat-tool/atomic-chat-mcp-stdio.ts container/agent-runner/src/atomic-chat-mcp-stdio.ts
Register the MCP server in the agent-runner
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 247 lines · 33 tokens per session scan A 9ab3c326ed55
add-atomic-chat-tool is a skill published in the GitHub repository taslim/nanoclaw-gws-ea (11 stars, last pushed 3mo ago), licensed MIT. It adds 33 tokens to every session and 2,215 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.
Other skills, from other repositories
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…
training-check
Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.