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 skills add johnku2011/boilerplates-with-ai-skills --skill code-reviewgit clone --depth 1 https://github.com/johnku2011/boilerplates-with-ai-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/johnku2011/boilerplates-with-ai-skills/code-review)<a href="https://agentmods.dev/skills/johnku2011/boilerplates-with-ai-skills/code-review"><img src="https://agentmods.dev/badge/skills/johnku2011/boilerplates-with-ai-skills/code-review/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/skills/johnku2011/boilerplates-with-ai-skills/code-review"><img src="https://agentmods.dev/badge/skills/johnku2011/boilerplates-with-ai-skills/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 79 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00028 | $0.00625 |
| Opus 5 | $0.00014 | $0.00313 |
| Sonnet 5 | $0.00006 | $0.00125 |
| Haiku 4.5 | $0.00003 | $0.00063 |
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 13d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Overview
Give a focused, constructive review of a change. Separate blocking issues from optional suggestions. Review the work product (diff + tests), not the author's process.
Core principle: Review early, review often — before merge, not after production.
When to Review
Mandatory:
- Before merging to the main branch
- After completing a major feature or multi-file change
- When security-sensitive paths change (auth, payments, user data)
Valuable:
- After fixing a non-trivial bug (regression check)
- Before a large refactor (baseline sanity check)
Process
- Read the change description and confirm it matches the diff.
- Identify scope: which files, routes, or modules changed and why.
- Check correctness: edge cases, error handling, and inputs that could break.
- Check tests: is new behavior covered? Do existing tests still pass?
- Check readability: clear names, small functions, no dead code.
- Check boundaries: server-only code must not leak to client bundles or logs.
- Note security concerns as blocking (see
project-securityskill).
Review Checklist
| Area | Blocking if… |
|---|---|
| Correctness | Wrong logic, missing error handling, race conditions |
| Tests | New behavior untested; tests deleted without replacement |
| Security | Unvalidated input, secrets in code/logs, missing auth |
| API shape | Breaking changes without migration or docs |
| Performance | Obvious N+1, unbounded loops, sync I/O on hot paths |
Output Format
Use this structure every time:
## Blocking
- [file:line] Issue — concrete fix
## Suggestions
- [file:line] Optional improvement
## Verdict
approve | approve-with-nits | request-changes
- List blocking issues first, each with a concrete fix.
- Then non-blocking suggestions.
- End with an explicit verdict.
Integration with TDD
If the change adds behavior without a failing test first, that is a blocking issue unless the author documents why (e.g. config-only change). Ask for tests that prove the behavior.
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.
- 13d ago First seen · 89 lines · 28 tokens per session scan A a6858b529dea
code-review is a skill published in the GitHub repository johnku2011/boilerplates-with-ai-skills (240 stars, last pushed 19d ago), licensed MIT. It adds 28 tokens to every session and 625 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
autoreview
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omh-code-review
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revdiff-plan
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code-reviewer
Code review specialist focused on patterns, bugs, security, and performance.
full-repo-review
Comprehensive four-wave review of all repo source files, producing a prioritized issue backlog.
agent-teams-simplify-and-harden
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or…