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/Qualimetry/claude-code-qualimetry-ai-appWrote 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/qualimetry/claude-code-qualimetry-ai-app/compliance-deps)<a href="https://agentmods.dev/commands/qualimetry/claude-code-qualimetry-ai-app/compliance-deps"><img src="https://agentmods.dev/badge/commands/qualimetry/claude-code-qualimetry-ai-app/compliance-deps/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/commands/qualimetry/claude-code-qualimetry-ai-app/compliance-deps"><img src="https://agentmods.dev/badge/commands/qualimetry/claude-code-qualimetry-ai-app/compliance-deps.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 | $0.00018 | $0.00283 |
| Opus 5 | $0.00009 | $0.00142 |
| Sonnet 5 | $0.00004 | $0.00057 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
compliance-deps 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 7d 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
Compliance: Deps
Invoke the bundled dependency-check skill. It walks four phases: assess (call get_dependency_vulnerabilities for the current branch), locate manifests in the workspace, resolve (apply each vulnerability's NextSafeVersion — auto for low-risk, propose for medium/high), and validate (run package restore + build).
Always upgrade to NextSafeVersion, not the latest version, to minimise breaking-change risk. The skill handles this - do not override.
The skill is suppression-aware. A CVE whose suppression request is still waiting for approval is reported, not fixed, so no effort goes into risk the organisation is already accepting. An approved suppression that expires within 15 days is flagged before the finding comes back. The CVEs a suppression has already removed from the report can be listed on request, with the scope, requester and reason behind each one. Raising and approving suppressions is a human step in the Qualimetry dashboard.
Requires Qualimetry Enterprise — if the MCP returns an "Enterprise feature" error, surface that to the user verbatim and stop.
If the MCP isn't configured, emit the verbatim self-healing message from /compliance-check.
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.
- 7d ago Changed · +2 lines · +3 tokens per session 55abbd24f068
- 12d ago First seen · 15 lines · 15 tokens per session scan A 3b5ada238e4d
compliance-deps is a command published in the GitHub repository Qualimetry/claude-code-qualimetry-ai-app (1 stars, last pushed 7d ago), licensed Apache-2.0. It adds 18 tokens to every session and 283 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 2026-08-31.
Other commands, from other repositories
ship
Branch, commit, open PR, gather Claude + every enabled AI reviewer (Copilot, CodeRabbit, etc.), fix/justify/resolve every finding, loop until clean, then merge. Run only when implementation is finished AND the owner has said to ship (e.g. "ship it") — never self-invoke just because the work looks done. To design and…
review
Multi-agent code review with parallel validation.
code-review-teach
Educational code review that teaches while reviewing. Provides constructive feedback, explains best practices, discusses trade-offs, and helps developers improve their coding skills.
hidden-dependencies
Discover hidden dependencies, implicit contracts, and non-obvious couplings in the codebase.
dead-code-scan
Scan for dead code, unused imports, duplicates, and zombie code across the project.
dead-code-clean
Actively find and remove dead code, unused imports, duplicates, and zombie code.