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/JSK9999/ai-nexusWrote 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/jsk9999/ai-nexus/review-checklist)<a href="https://agentmods.dev/agents/jsk9999/ai-nexus/review-checklist"><img src="https://agentmods.dev/badge/agents/jsk9999/ai-nexus/review-checklist/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/agents/jsk9999/ai-nexus/review-checklist"><img src="https://agentmods.dev/badge/agents/jsk9999/ai-nexus/review-checklist.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 | $0.00015 | $0.00464 |
| Opus 5 | $0.00008 | $0.00232 |
| Sonnet 5 | $0.00003 | $0.00093 |
| Haiku 4.5 | $0.00002 | $0.00046 |
Grade A, and why
Review Checklist 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 10d 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
Review Checklist
Code Quality
Size Limits
- File size ≤ 300 LOC
- Function size ≤ 50 LOC
- Parameters ≤ 5
- Cyclomatic complexity ≤ 10
- Split/refactor if limits exceeded
Clean Code
- Intention-revealing names used
- Each function does one thing
- Side effects isolated to boundary layers
- Guard clauses preferred
- Constants symbolized (no hardcoding)
- Code structured as Input → Processing → Return
Functionality Review
- Correctly implements requirements
- Edge cases handled
- Error handling is appropriate
- No unintended side effects
Security Review
- No secrets in code
- Inputs validated and sanitized
- No SQL injection vulnerabilities
- No XSS vulnerabilities
- Authentication/authorization applied
- See security-rules.md for full checklist
Testing Review
- New code has tests
- Bug fixes have regression tests
- Tests are deterministic
- E2E has success and failure paths
- See testing-rules.md for full checklist
Performance Review
- No obvious performance issues
- Database queries optimized
- No N+1 query problems
- Appropriate caching considered
Documentation Review
- Complex logic is documented
- API changes documented
- README updated if needed
- Breaking changes noted
Reviewer Actions
- Read: Understand the context and purpose
- Verify: Check against requirements
- Test: Run tests locally if needed
- Comment: Provide constructive feedback
- Approve/Request Changes: Make clear decision
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.
- 10d ago First seen · 71 lines · 15 tokens per session scan A ae5f00dc8ac9
Review Checklist is an agent published in the GitHub repository JSK9999/ai-nexus (19 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 15 tokens to every session and 464 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 agents, from other repositories
fresh-eyes
Clean-context design reviewer. Reviews just-written code changes with zero memory of writing them — catches half-finished changes and cross-file drift (a file updated but the file pointing at it left stale), then over-engineering, scope creep, and simpler alternatives: the judgment calls hooks and checklists cannot…
proof-eyes
An evidence checker for possible duplicate-code findings from a repository scan. It opens the actual code and decides whether each scanner result is a real duplicate, a false alarm, or uncertain.
code-standards-enforcer
Use this agent to analyze code files against code quality standards after edits are made. This agent should be triggered proactively after code modifications when code-standards plugin is active. Context: The code-standards plugin is enabled and the user just finished writing a new TypeScript file. user: "I've added…
api-analyzer
Analyze API endpoints, REST/GraphQL design, and client-server communication for over-fetching, missing pagination, or inefficient endpoint design. Use when user asks about API performance or runs /n1-optimizer:analyze.
database-analyzer
Analyze database queries, ORM usage, and data access patterns for N+1 queries, missing indexes, or inefficient JOINs. Use when user asks about database performance or runs /n1-optimizer:analyze.
code-verifier
Verifies repository-backed claims and implementation feasibility in PRDs, Design Docs, or Work Plans. Use before document review, after implementation, or for reverse-engineered artifact verification.