NanoClaw is an AI assistant that runs agents inside separate Linux containers, isolating their files and execution environments. People use it to connect agents to messaging services and run assistants with memory and scheduled jobs. The catalogue contains skills and instructions for extending or operating NanoClaw.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nanocoai/nanoclaw --skill add-dashboardgit clone --depth 1 https://github.com/nanocoai/nanoclawWrote 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/nanocoai/nanoclaw/add-dashboard)<a href="https://agentmods.dev/skills/nanocoai/nanoclaw/add-dashboard"><img src="https://agentmods.dev/badge/skills/nanocoai/nanoclaw/add-dashboard/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/nanocoai/nanoclaw/add-dashboard"><img src="https://agentmods.dev/badge/skills/nanocoai/nanoclaw/add-dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk fail
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Tool Misuse · line 116 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.
- high Privilege Escalation · line 58 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00032 | $0.01356 |
| Opus 5 | $0.00016 | $0.00678 |
| Sonnet 5 | $0.00006 | $0.00271 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
add-dashboard 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 11d 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://localhost:3100/api/status How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/add-dashboard — NanoClaw Dashboard
Adds a local monitoring dashboard showing agent groups, sessions, channels, users, token usage, context windows, message activity, and real-time logs.
Architecture
NanoClaw (pusher) Dashboard (npm package)
┌──────────┐ POST JSON ┌──────────────┐
│ collects │ ────────────────→ │ /api/ingest │
│ DB data │ every 60s │ in-memory │
│ tails │ ────────────────→ │ /api/logs/ │
│ log file │ every 2s │ push │
└──────────┘ │ serves UI │
└──────────────┘
Steps
1. Install the npm package
pnpm install @nanoco/nanoclaw-dashboard
2. Copy the pusher module and its tests
Copy all three resource files into src/. The tests ship with the skill and run against the composed project — they're how you confirm the skill works and is wired in correctly.
.claude/skills/add-dashboard/resources/dashboard-pusher.ts → src/dashboard-pusher.ts
.claude/skills/add-dashboard/resources/dashboard-pusher.test.ts → src/dashboard-pusher.test.ts
.claude/skills/add-dashboard/resources/dashboard-wiring.test.ts → src/dashboard-wiring.test.ts
dashboard-pusher.test.ts— behavior: starts the pusher, posts a real snapshot to a fake dashboard.dashboard-wiring.test.ts— the code edit in step 3: asserts (via the TS AST) thatindex.tsdynamically imports./dashboard-pusher.jsandawaitsstartDashboard()as colocated statements ofmain(), after DB init and before the boot-complete log. Delete or misplace the edit and this goes red.
3. Wire into src/index.ts
This is the skill's one integration point, and it's deliberately minimal and self-contained: all the startup logic lives in dashboard-pusher.ts, and the import is colocated with the call so the whole edit is a single block in one place — there's no separate top-of-file import to add (or to remember to remove).
Add this block inside main(), just before the log.info('NanoClaw running') line:
What ships with it
3 files 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.
- 11d ago First seen · 125 lines · 32 tokens per session scan A f44df22fcae2
add-dashboard is a skill published in the GitHub repository nanocoai/nanoclaw (30,736 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 1,356 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
Pynchy Development
Use when running pynchy locally — running the app, tests, linting, formatting, prek hooks, or rebuilding the agent container. Also use when determining whether you're on the live Pynchy host or a local machine, and for debugging agent behavior-- session transcript branching, inspecting message history and agent traces…
Pynchy Plugin Authoring
Use when creating, scaffolding, or updating a pynchy plugin, including channels, MCP servers, skills, agent cores, workspace specs, and container runtime plugins. Also use when users ask how to register plugins via config.toml, add entry points, or validate plugin hook wiring.
slack-token-extractor
Refresh expired Slack browser tokens (xoxc/xoxd) using persistent browser sessions. Use when Slack MCP tools fail with authentication errors.
x-integration
Post tweets, like, reply, retweet, and quote on X (Twitter) using browser automation. Use when the user asks you to interact with X/Twitter.
Documentation Manager
Use when writing or reviewing pynchy documentation, deciding where to document things, updating the docs, checking doc consistency, or fixing broken links. Covers information architecture, writing philosophy, tree-shaped navigation, doc-code coupling, no hard-coded usernames, extensibility framing for pluggable…
python-heredoc
When running multi-line Python code or code with quotes, apostrophes, or f-strings via Bash, always use heredoc syntax instead of python -c to avoid shell quoting issues.