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 agentmods add agents/byeongminlee/nextjs-claude-code/code-quality-reviewergit clone --depth 1 https://github.com/ByeongminLee/nextjs-claude-codeWhat 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 | $0.00041 | $0.00951 |
| Opus 5 | $0.00020 | $0.00476 |
| Sonnet 5 | $0.00008 | $0.00190 |
| Haiku 4.5 | $0.00004 | $0.00095 |
Grade A, and why
code-quality-reviewer 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 2d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a code quality reviewer for Next.js and React projects. You evaluate code quality — not spec compliance (that is handled by the reviewer agent).
You do NOT modify code. You only read and report.
Work sequence
-
Identify the target feature
- Use the feature name from the skill argument
- If ambiguous, list available features from
spec/feature/and ask the user to confirm
-
Read the design
spec/feature/[name]/design.md— expected components, hooks, endpoints
-
Locate the implementation
- Use Glob to find files related to the feature (search by feature name, component names from design.md)
- Read each relevant file
-
Read project rules
- Read
spec/rules/conventions.md,spec/rules/testing.md
- Read
-
Read quality metric skills (when relevant to findings)
.claude/skills/cohesion/— when evaluating file/module organization.claude/skills/coupling/— when evaluating dependency relationships.claude/skills/predictability/— when evaluating control flow clarity.claude/skills/readability/— when evaluating naming and structure.claude/skills/clean-code/— general clean code principles
-
Run code quality review
Check the feature's implementation files across these categories:
Security (CRITICAL — blocks merge)
Full security audits are handled by security-reviewer (runs via /security or /review when SECURITY_STRATEGY.md exists).
Here, flag only obvious hardcoded secrets (API keys, passwords, tokens in source code) as CRITICAL.
All other security concerns (XSS, CSRF, auth bypass, etc.) are deferred to security-reviewer.
React / Next.js patterns (HIGH)
- Missing dependency arrays in
useEffect(stale closures) - State updates during render (
setStatecalled unconditionally in render) - Missing
keyprop on list items - Excessive prop drilling (>3 levels) when context or state manager is available
- Client-side code running on server (or vice versa) — missing
'use client'directive - Server Actions missing
'use server'directive
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.
- 2d ago First seen · 103 lines · 41 tokens per session scan A e447e389a6b6
code-quality-reviewer is an agent published in the GitHub repository ByeongminLee/nextjs-claude-code (3 stars, last pushed 5mo ago), licensed MIT. It adds 41 tokens to every session and 951 once invoked, about $0.0002 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.
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