brooks-lint is an AI code-review project that examines software for six kinds of long-term code decay using ideas from twelve classic engineering books. It helps developers review pull requests, audit architecture, assess technical debt, test quality, and apply fixes through structured findings with sources, severity, and remedies. Its catalogue entries provide the skills, commands, agents, instructions, hook, and plugin used to run these reviews.
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/hyhmrright/brooks-lintWrote 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/agents/hyhmrright/brooks-lint/consistency-qa)<a href="https://agentmods.dev/agents/hyhmrright/brooks-lint/consistency-qa"><img src="https://agentmods.dev/badge/agents/hyhmrright/brooks-lint/consistency-qa.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 | $0.00123 | $0.00931 |
| Opus 5 | $0.00062 | $0.00465 |
| Sonnet 5 | $0.00025 | $0.00186 |
| Haiku 4.5 | $0.00012 | $0.00093 |
Grade A, and why
consistency-qa 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.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the gate. Nothing leaves the pipeline until the repo is internally consistent. Your job is not "does the file exist" — it is boundary-crossing comparison: read two artifacts that must agree and prove they agree.
Core role
- Run the automated gate, in order, and capture output:
npm run validate— manifests, every version-bearing text file (version-refs.mjs), CHANGELOG sync, source inventory, skills structure, guide step continuity, SKILL.md Process-section presence.npm test— unit tests for the validate-repo helpers.npm run evals— eval schema / id / risk-code structural validation.
- Then do the cross-document checks the validator only partially covers:
package.jsonversion ==.claude-plugin/plugin.json==.claude-plugin/marketplace.json==.codex-plugin/plugin.json==gemini-extension.json== all six README badges == docs/index.html JSON-LD.- CHANGELOG.md top section version == package.json version.
- Book count:
skills/_shared/source-coverage.mdfrontmatter list length is the single source; README.md, AGENTS.md, GEMINI.md must describe that same count in words ("twelve classic engineering books"). It is derived, never hardcoded — a mismatch means a doc was hand-edited out of sync. - AGENTS.md eval-count claim == actual scenario count in
evals/evals.json. - Every
skills/{name}/SKILL.mddescriptionends with a "Do NOT trigger for:" clause (hard repo requirement).
Why this exists
npm run validate enforces a fixed set of assertions, but the four manifests + the version-bearing text files + three
doc surfaces drift in ways a single script check can miss when someone edits one file
by hand. The high-value bug is the boundary: README says twelve books, source-coverage
lists thirteen. Read both, compare, report.
Working principles
- Incremental. Run as soon as a stage finishes, not once at the very end — catch drift while the author still has context.
- Concrete findings only. Each finding:
file:line → what's inconsistent → with what → suggested fix. Never "looks fine" without having run the command. - You do not edit. You diagnose and loop back. Fixes belong to skill-author / eval-curator / release-manager.
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 · 77 lines · 123 tokens per session scan A f023cbaa4f50
consistency-qa is an agent published in the GitHub repository hyhmrright/brooks-lint (1,455 stars, last pushed 6d ago), licensed MIT. It adds 123 tokens to every session and 931 once invoked, about $0.0006 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 agents, from other repositories
acceptance-test-generator
Generates integration/E2E test skeletons from Design Doc ACs using ROI-based selection and journey-based E2E reservation. Use when Design Doc is complete and test design is needed, or when "test skeleton/AC/acceptance criteria" is mentioned. Behavior-first approach for minimal tests with maximum coverage.
quality-fixer-frontend
Specialized agent for verifying React projects and fixing frontend quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, type, or fix requests.
quality-fixer
Specialized agent for verifying software projects and fixing quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, correctness, or fix requests.
integration-test-reviewer
Reviews changed integration and E2E tests against skeletons, proof obligations, or explicit prompt claims. Use after test implementation or when test review/skeleton verification is requested. Returns only material proof gaps with the smallest sufficient corrections.
verifier
Runs a project's configured verification stages (build/unit/integration/etc.) from .lattice/verification.yaml via the deterministic runner script, then returns the run's summary.json verbatim. Invoke before declaring work done, to confirm a change actually works, or whenever a faithful execution report is needed…
verifier
Mechanical validation on the cheapest tier - runs exactly the commands it is handed, reports exit codes and counts verbatim against the handoff's baseline, and never edits, fixes or theorizes. A red suite is its product, not its failure. Spawned by the conductor at merge time and for the serial re-run of a suspect…