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 ArieGoldkin/ai-agent-hub --skill code-review-playbookgit clone --depth 1 https://github.com/ArieGoldkin/ai-agent-hubWrote 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/ariegoldkin/ai-agent-hub/code-review-playbook)<a href="https://agentmods.dev/skills/ariegoldkin/ai-agent-hub/code-review-playbook"><img src="https://agentmods.dev/badge/skills/ariegoldkin/ai-agent-hub/code-review-playbook/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/ariegoldkin/ai-agent-hub/code-review-playbook"><img src="https://agentmods.dev/badge/skills/ariegoldkin/ai-agent-hub/code-review-playbook.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 | $0.00046 | $0.06197 |
| Opus 5 | $0.00023 | $0.03099 |
| Sonnet 5 | $0.00009 | $0.01239 |
| Haiku 4.5 | $0.00005 | $0.00620 |
Grade A, and why
code-review-playbook 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.
How it starts
The opening of the file, as written. The whole thing — 917 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Playbook
Overview
This skill provides a comprehensive framework for effective code reviews that improve code quality, share knowledge, and foster collaboration. Whether you're a reviewer giving feedback or an author preparing code for review, this playbook ensures reviews are thorough, consistent, and constructive.
When to use this skill:
- Reviewing pull requests or merge requests
- Preparing code for review (self-review)
- Establishing code review standards for teams
- Training new developers on review best practices
- Resolving disagreements about code quality
- Improving review processes and efficiency
Code Review Philosophy
Purpose of Code Reviews
Code reviews serve multiple purposes:
- Quality Assurance: Catch bugs, logic errors, and edge cases
- Knowledge Sharing: Spread domain knowledge across the team
- Consistency: Ensure codebase follows conventions and patterns
- Mentorship: Help developers improve their skills
- Collective Ownership: Build shared responsibility for code
- Documentation: Create discussion history for future reference
Principles
Be Kind and Respectful:
- Review the code, not the person
- Assume positive intent
- Praise good solutions
- Frame feedback constructively
Be Specific and Actionable:
- Point to specific lines of code
- Explain why something should change
- Suggest concrete improvements
- Provide examples when helpful
Balance Speed with Thoroughness:
- Aim for timely feedback (< 24 hours)
- Don't rush critical reviews
- Use automation for routine checks
- Focus human review on logic and design
Distinguish Must-Fix from Nice-to-Have:
- Use conventional comments to indicate severity
- Block merges only for critical issues
- Allow authors to defer minor improvements
- Capture deferred work in follow-up tickets
Conventional Comments
A standardized format for review comments that makes intent clear.
Format
<label> [decorations]: <subject>
[discussion]
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 917 lines · 46 tokens per session scan A d27150a7c905
code-review-playbook is a skill published in the GitHub repository ArieGoldkin/ai-agent-hub (11 stars, last pushed 9mo ago), licensed MIT. It adds 46 tokens to every session and 6,197 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 2026-08-30.
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