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 majiang213/OpenClaw-MAS --skill cmd_clawgit clone --depth 1 https://github.com/majiang213/OpenClaw-MASWrote 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/majiang213/openclaw-mas/cmd_claw)<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/cmd_claw"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/cmd_claw/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/majiang213/openclaw-mas/cmd_claw"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/cmd_claw.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 | $0.00022 | $0.00293 |
| Opus 5 | $0.00011 | $0.00147 |
| Sonnet 5 | $0.00004 | $0.00059 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
cmd_claw 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 8d 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.
What it actually says
Project Path
The first argument is the project path. Before doing anything else:
- Extract the project path from the first argument
- Verify the path exists
- Work within that directory for all file operations and shell commands
Claw Command (Legacy Shim)
Use this only if you still reach for /claw from muscle memory. The maintained implementation lives in skills/nanoclaw-repl/SKILL.md.
Canonical Surface
- Prefer the
nanoclaw-replskill directly. - Keep this file only as a compatibility entry point while command-first usage is retired.
Arguments
$ARGUMENTS
Delegation
Apply the nanoclaw-repl skill and keep the response focused on operating or extending scripts/claw.js.
- If the user wants to run it, use
node scripts/claw.jsornpm run claw. - If the user wants to extend it, preserve the zero-dependency and markdown-backed session model.
- If the request is really about long-running orchestration rather than NanoClaw itself, redirect to
dmux-workflowsorautonomous-agent-harness.
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.
- 8d ago First seen · 36 lines · 22 tokens per session scan A a06b7e31165a
cmd_claw is a skill published in the GitHub repository majiang213/OpenClaw-MAS (5 stars, last pushed 5mo ago), licensed MIT. It adds 22 tokens to every session and 293 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
sequence-diagram
Show interactions and flows over time. Illustrate request paths, asynchronous patterns, error handling. Use when documenting complex flows or onboarding on system behavior.
architecture-anti-patterns
Identify and avoid common architectural mistakes. Recognize patterns of failure. Use when reviewing designs or learning from mistakes.
architecture-patterns-catalog
Reference catalog of proven architecture patterns. Know when to apply each pattern, tradeoffs, and examples. Use as reference when designing systems.
system-audit
Conduct comprehensive system architecture evaluation. Assess design quality, technical debt, operational readiness, scalability. Use when auditing existing systems.
storage-selection
Choose the right database technology for specific workloads. Evaluate relational, NoSQL, data warehouses, and search engines. Use when selecting storage systems for new features or optimizing existing ones.
architecture-review-facilitation
Lead effective architecture reviews. Manage discussions, surface disagreements, build consensus, document decisions. Use when conducting reviews or running architecture forums.