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 skills/developersglobal/ai-agent-skills/code-reviewnpx skills add DevelopersGlobal/ai-agent-skills --skill code-reviewgit clone --depth 1 https://github.com/DevelopersGlobal/ai-agent-skillsWrote 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/skills/developersglobal/ai-agent-skills/code-review)<a href="https://agentmods.dev/skills/developersglobal/ai-agent-skills/code-review"><img src="https://agentmods.dev/badge/skills/developersglobal/ai-agent-skills/code-review.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 | $0.00028 | $0.00681 |
| Opus 5 | $0.00014 | $0.00341 |
| Sonnet 5 | $0.00006 | $0.00136 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
code-review 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 4d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Code review is the last line of defense before code reaches production. This skill structures the review process to catch real issues — not just style preferences — and ensures every comment is actionable and proportionate.
When to Use
- Before merging any pull request
- When reviewing AI-generated code
- When auditing existing code for quality
Process
Step 1: Understand the Change
- Read the PR description fully — understand the intent before reading code.
- Check: Does the implementation match the stated intent?
- Identify the risk level: data mutation? auth changes? public API?
Verify: You understand what the PR is trying to accomplish.
Step 2: Correctness Review
- Does the code do what it claims to do?
- Are there off-by-one errors, null dereferences, or race conditions?
- Are all error cases handled?
- Do tests cover the happy path AND key failure paths?
Verify: You can trace the execution path for the primary use case and 2 failure cases.
Step 3: Security Review
- Apply security-hardening skill to any auth/input/data changes.
- Does this change open any OWASP Top 10 vulnerabilities?
- Are any secrets or PII handled correctly?
Step 4: Maintainability Review
- Will the next developer understand this code without the author present?
- Are functions doing one thing?
- Are names descriptive and accurate?
- Is complexity proportionate to the problem?
Step 5: Provide Actionable Feedback
- Every comment must be one of:
- Blocker: Must be fixed before merge
- Suggestion: Optional improvement
- Question: Needs clarification (not necessarily a problem)
- Blockers must be specific: "This SQL query is vulnerable to injection via
{username}— use parameterized queries." - Never leave vague comments like "this doesn't look right" without explaining why.
Common Rationalizations (and Rebuttals)
| Excuse | Rebuttal |
|---|---|
| "I'll review it quickly" | A rushed review is not a review. Take the time or ask someone who can. |
| "The tests pass so it's fine" | Tests prove the code works for tested inputs, not that it's secure or maintainable. |
| "I'll comment on style later" | Style comments without blocker separation waste everyone's time. Label them. |
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.
- 4d ago First seen · 80 lines · 28 tokens per session scan A af599abf58fe
code-review is a skill published in the GitHub repository DevelopersGlobal/ai-agent-skills (65 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 681 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 skills, from other repositories
code-review-and-quality
Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.
constraint-driven-development
Establishes a project's quality bar as a written contract and stops agents quietly lowering it. Interviews the user on which dimensions matter, supplies sane default thresholds when they have no number in mind, records everything in CONSTRAINTS.md, and watches the diff for a weakened bar — new @ts-ignore or…
performance-optimization
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
api-and-interface-design
Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
code-simplification
Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production, security-sensitive logic, irreversible operations), or any time a confident output would be cheaper to verify now…