Borrowing it
Nothing to install: this file belongs to systemowiec/ai-agents-workspace-starter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/systemowiec/ai-agents-workspace-starter/main/.claude/commands/audit.mdgit clone --depth 1 https://github.com/systemowiec/ai-agents-workspace-starterWrote 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/systemowiec/ai-agents-workspace-starter/audit)<a href="https://agentmods.dev/commands/systemowiec/ai-agents-workspace-starter/audit"><img src="https://agentmods.dev/badge/commands/systemowiec/ai-agents-workspace-starter/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 | $0.00008 | $0.00175 |
| Opus 5 | $0.00004 | $0.00088 |
| Sonnet 5 | $0.00002 | $0.00035 |
| Haiku 4.5 | $0.00001 | $0.00017 |
Grade A, and why
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
Run quality-gate subagent.
- Read
.agents/roles/quality-gate.md- scoring system and checklist - Read
AGENTS.md- global rules - Read
.agents/learnings/gotchas.md- known gotchas - Ask user for scope: last commit / feature X / full audit
- Perform scoring according to 6 categories (architecture, security, tests, quality, contracts, docs)
- Save report in
docs/specs/{layer}/{PREFIX}-NNN/review-{role}.md - If you found a gotcha - propose an entry to
.agents/learnings/gotchas.md
IMPORTANT: Always run as a separate subagent (readonly). NEVER audit code you wrote yourself in the same session.
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 · 17 lines · 8 tokens per session scan A 0ca901f8db98
audit is a command published in the GitHub repository systemowiec/ai-agents-workspace-starter (2 stars, last pushed 5mo ago), licensed MIT. It adds 8 tokens to every session and 175 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.
argos
A command for checking whether an implementation matches its design deliverables. Its Korean description compares the work to the design as part of a completion inspection.