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 manage-channelsgit 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/manage-channels)<a href="https://agentmods.dev/skills/nanocoai/nanoclaw/manage-channels"><img src="https://agentmods.dev/badge/skills/nanocoai/nanoclaw/manage-channels/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/manage-channels"><img src="https://agentmods.dev/badge/skills/nanocoai/nanoclaw/manage-channels.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Excessive Agency · line 129 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.02373 |
| Opus 5 | $0.00017 | $0.01187 |
| Sonnet 5 | $0.00007 | $0.00475 |
| Haiku 4.5 | $0.00003 | $0.00237 |
Grade A, and why
manage-channels scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Manage Channels
Wire messaging channels to agent groups. See docs/isolation-model.md for the full isolation model.
Privilege is a user-level concept, not a channel-level one (see src/modules/permissions/db/user-roles.ts, src/modules/permissions/access.ts). There is no "main channel" / "main group" — any user can be granted owner or admin (global or scoped to an agent group) via grantRole(), and messages from unknown senders are gated per-messaging-group by unknown_sender_policy (strict | request_approval | public).
Assess Current State
Read the central DB (data/v2.db) using these canonical queries (column names match the schema, not the CLI flags — the register command's --assistant-name is stored in agent_groups.name).
Run each via the in-tree wrapper — the host setup deliberately ships no sqlite3 CLI:
pnpm exec tsx scripts/q.ts data/v2.db "<query>"
SELECT id, name AS assistant_name, folder, agent_provider FROM agent_groups;
SELECT id, channel_type, platform_id, name, unknown_sender_policy FROM messaging_groups;
SELECT messaging_group_id, agent_group_id, engage_mode, engage_pattern, session_mode, threads, priority FROM messaging_group_agents;
SELECT user_id, role, agent_group_id FROM user_roles ORDER BY role='owner' DESC;
Also check .env for channel tokens and src/channels/index.ts for uncommented imports.
Categorize channels as: wired (has DB entities + messaging_group_agents row), configured but unwired (has credentials + barrel import, no DB entities), or not configured.
If the instance has no owner yet (SELECT COUNT(*) FROM user_roles WHERE role='owner' AND agent_group_id IS NULL returns 0), tell the user they should run /init-first-agent first — it stands up the first agent group, promotes the operator to owner, and verifies delivery end-to-end by having the agent DM them. Then return here for any additional channels/groups.
First Channel (No Agent Groups Exist)
Delegate to /init-first-agent. It handles: channel choice, operator identity lookup, DM platform id resolution (with cold-DM or pair-code fallback), agent group creation, wiring, and the welcome DM. Return here afterward for any additional channels.
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 · 149 lines · 34 tokens per session scan A 00156c70c80b
manage-channels is a skill published in the GitHub repository nanocoai/nanoclaw (30,736 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 2,373 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. 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.
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.
slack-token-extractor
Refresh expired Slack browser tokens (xoxc/xoxd) using persistent browser sessions. Use when Slack MCP tools fail with authentication errors.
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.