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
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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-rtk)<a href="https://agentmods.dev/skills/nanocoai/nanoclaw/add-rtk"><img src="https://agentmods.dev/badge/skills/nanocoai/nanoclaw/add-rtk/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-rtk"><img src="https://agentmods.dev/badge/skills/nanocoai/nanoclaw/add-rtk.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 | $0.00048 | $0.01226 |
| Opus 5 | $0.00024 | $0.00613 |
| Sonnet 5 | $0.00010 | $0.00245 |
| Haiku 4.5 | $0.00005 | $0.00123 |
Grade D, and why
add-rtk scanned grade D with 3 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 9d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://raw.githubusercontent.com/rtk-ai/rtk/refs/heads/master/install.sh | sh Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
This file is mounted at `/home/node/.claude/settings.json` inside the container and is read by Claude Code for hooks, env, and model config. Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://raw.githubusercontent.com/rtk-ai/rtk/refs/heads/master/install.sh | sh How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add rtk
Install rtk — a CLI proxy delivering 60–90% token savings on common dev commands (git, cargo, pytest, docker, kubectl, etc.) — and wire it transparently into agent containers via the Claude Code PreToolUse hook.
What this sets up
rtkbinary at~/.local/bin/rtkon the host~/.local/bin/rtkmounted read-only at/usr/local/bin/rtkinside the target agent group's containersPreToolUsehook in the agent group'ssettings.jsonso every Bash call is automatically filtered through rtk — no CLAUDE.md instructions needed
Integration tests
This skill has no in-tree integration test by design. Its only functional reach-ins are runtime operator actions — the host-only ncl groups config add-mount (Step 3) and the settings.json PreToolUse hook write (Step 4) — neither of which leaves a line in the source tree whose deletion a test could catch. There are no package dependencies or Dockerfile edits to guard either. Conformance is idempotent apply + REMOVE.md; the mount and hook are verified at runtime (see Verify).
Step 1 — Install rtk on the host
curl -fsSL https://raw.githubusercontent.com/rtk-ai/rtk/refs/heads/master/install.sh | sh
If the script put the binary elsewhere, move it:
find ~/.local ~/.cargo/bin ~/bin -name rtk 2>/dev/null
mv "$(which rtk 2>/dev/null)" ~/.local/bin/rtk
Verify:
~/.local/bin/rtk --version
chmod +x ~/.local/bin/rtk # if needed
Step 2 — Identify the target agent group
ncl groups list
Note the group ID (e.g. ag-1776342942165-ptgddd). Repeat Steps 3–5 for each group.
Step 3 — Mount rtk into the container config
Mount the host rtk binary read-only into the container with the host-only add-mount verb. It is idempotent — re-running skips the entry if it is already present:
ncl groups config add-mount --id <group-id> \
--host ~/.local/bin/rtk \
--container /usr/local/bin/rtk \
--ro
This verb is operator-only and runs host-side (via /setup, /customize, or /manage-mounts); it is rejected from inside a container.
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.
- 9d ago First seen · 138 lines · 48 tokens per session scan D 6f08d5f309ad
add-rtk is a skill published in the GitHub repository nanocoai/nanoclaw (30,720 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 1,226 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it D with 3 findings (downloads and executes remote code, reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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