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.
git clone --depth 1 https://github.com/paladini/harness-scoreWrote 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/commands/paladini/harness-score/harness-audit)<a href="https://agentmods.dev/commands/paladini/harness-score/harness-audit"><img src="https://agentmods.dev/badge/commands/paladini/harness-score/harness-audit.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 | $0.00014 | $0.00334 |
| Opus 5 | $0.00007 | $0.00167 |
| Sonnet 5 | $0.00003 | $0.00067 |
| Haiku 4.5 | $0.00001 | $0.00033 |
Grade A, and why
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 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
/harness-audit
Audit this repository's AI harness maturity. Follow these steps exactly:
-
Run the deterministic scanner from the workspace root:
npx -y harness-score . --jsonDo not analyze the repository yourself — the scanner's output is the audit. It is fully deterministic (filesystem checks only, no AI, no network), so its numbers are reproducible facts.
-
Present the results to the user:
- The maturity level (
level.index,level.name) and total score, with one sentence of interpretation. - A compact table of the six dimensions with their percentages.
- The top 3 failed checks by points (
checks[]wherepassedis false, sorted bypointsdescending): for each, give the check id, what is missing (evidence), the concrete fix (remediation), and the guide link (docsUrl). - If
level.nextLevelGapsis non-empty, state exactly what blocks the next level.
- The maturity level (
-
End by offering: "Want me to fix any of these? I can create the missing harness files following the guide's recipes." If the user accepts, use the harness-engineering skill.
If npx fails (offline/registry blocked), say so and suggest installing the
CLI locally with npm i -D harness-score; never substitute your own
estimate for the scanner's output.
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 · 37 lines · 14 tokens per session scan A 9b6204cb9b89
harness-audit is a command published in the GitHub repository paladini/harness-score (398 stars, last pushed yesterday), licensed MIT. It adds 14 tokens to every session and 334 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 2026-08-30.
Other commands, from other repositories
README
Custom commands are reusable prompt templates you invoke with /command-name in Claude Code.
extract-profile
Extract a complete profile from an existing repo (runs the extract-profile skill).
rfc
Scaffold a new RFC in docs/rfc/proposed/.
review
Review the current changes with the code-reviewer subagent.
squadai-init
You are running the squadai squadai-init routine: read the current repository, understand what it actually contains, and refine each configured agent's role files (or solo instructions file) so they are tuned to this codebase — without losing any methodology semantics squadai installed.
memory-add
Capture a decision, learning, or incident note into project memory.