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 agentmods add skills/nanocoai/nanoclaw/customizenpx skills add nanocoai/nanoclaw --skill customizegit 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/customize)<a href="https://agentmods.dev/skills/nanocoai/nanoclaw/customize"><img src="https://agentmods.dev/badge/skills/nanocoai/nanoclaw/customize.svg" alt="Measured on agentmods" 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 | $0.00060 | $0.01600 |
| Opus 5 | $0.00030 | $0.00800 |
| Sonnet 5 | $0.00012 | $0.00320 |
| Haiku 4.5 | $0.00006 | $0.00160 |
Grade A, and why
customize 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 6d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NanoClaw Customization
This skill helps users add capabilities or modify behavior. Use AskUserQuestion to understand what they want before making changes.
Workflow
- Understand the request — Ask clarifying questions.
- Prefer a dedicated skill — If a skill covers the request, invoke it instead of editing core by hand:
- Channels:
/add-telegram,/add-slack,/add-discord,/add-whatsapp,/add-signal,/add-imessage, and the rest of the/add-<channel>family. - Wiring channels to agents and isolation levels:
/manage-channels. - Container directory access:
/manage-mounts. - Agent providers (non-default):
/add-opencode,/add-codex,/add-ollama-provider. - MCP tools:
/add-ollama-tool,/add-atomic-chat-tool.
- Channels:
- Plan the changes — Identify the v2 surface the change belongs to (entity model in the central DB, per-agent-group container config, per-group
CLAUDE.md, or core code). - Implement — Make the change on the right surface.
- Test guidance — Tell the user how to verify.
Entity Model
Customizations route through the v2 entity model: users → messaging groups → agent groups → sessions. A messaging group is one chat/channel on one platform; an agent group holds the workspace, personality, and container config; a wiring links a messaging group to an agent group with a session mode and trigger rules. Inspect and edit all of this with the ncl admin CLI. See docs/isolation-model.md for the three isolation levels.
Key Files
| File | Purpose |
|---|---|
src/index.ts |
Entry point: init DB, migrations, channel adapters, delivery polls, sweep, shutdown |
src/router.ts |
Inbound routing: messaging group → agent group → session → inbound.db → wake |
src/delivery.ts |
Polls outbound.db, delivers via adapter, handles system actions |
src/session-manager.ts |
Resolves sessions; opens inbound.db / outbound.db; heartbeat path |
src/container-runner.ts |
Spawns per-agent-group containers with session DB + outbox mounts, OneCLI ensureAgent |
src/channels/ |
Channel adapter infra (registry, Chat SDK bridge); specific adapters install from the channels branch |
src/config.ts |
Process-level config (assistant name, paths, timeouts) read from .env |
data/v2.db |
Central DB: users, roles, agent_groups, messaging_groups, wirings, container_configs |
data/v2-sessions/<session>/ |
Per-session inbound.db (host→container) + outbound.db (container→host) |
groups/<folder>/CLAUDE.md |
Per-agent-group memory/persona and instructions |
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.
- 6d ago First seen · 127 lines · 60 tokens per session scan A 8dfd0954bb83
customize is a skill published in the GitHub repository nanocoai/nanoclaw (30,701 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 1,600 once invoked, about $0.0003 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.
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…
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.
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.