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_harness_auditgit 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_harness_audit)<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/cmd_harness_audit"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/cmd_harness_audit/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_harness_audit"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/cmd_harness_audit.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 | $0.00026 | $0.00241 |
| Opus 5 | $0.00013 | $0.00120 |
| Sonnet 5 | $0.00005 | $0.00048 |
| Haiku 4.5 | $0.00003 | $0.00024 |
Grade A, and why
cmd_harness_audit 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 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.
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
Delegate to the harness-optimizer agent.
Include in the task payload:
- Project path (the absolute path the user provided as the first argument)
- Scope: repo (full), hooks, skills, commands, or agents (default: repo)
- Output format preference: text (default) or json
- Any known issues or areas of concern to prioritize
First, reply to the user briefly to confirm you are delegating to harness-optimizer.
Then call sessions_spawn:
{
"agentId": "harness-optimizer",
"sessionKey": "harness-optimizer",
"task": "<user's full request and all relevant context — the agent cannot see this conversation>",
"runTimeoutSeconds": 0
}
After sessions_spawn returns, relay the result to the user. Do not output anything after the spawn call until the result arrives.
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 · 32 lines · 26 tokens per session scan A 6ec136e41946
cmd_harness_audit is a skill published in the GitHub repository majiang213/OpenClaw-MAS (5 stars, last pushed 5mo ago), licensed MIT. It adds 26 tokens to every session and 241 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.