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 caipe-io/ai-platform-engineering --skill review-specific-prgit clone --depth 1 https://github.com/caipe-io/ai-platform-engineeringWrote 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/caipe-io/ai-platform-engineering/review-specific-pr)<a href="https://agentmods.dev/skills/caipe-io/ai-platform-engineering/review-specific-pr"><img src="https://agentmods.dev/badge/skills/caipe-io/ai-platform-engineering/review-specific-pr/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/caipe-io/ai-platform-engineering/review-specific-pr"><img src="https://agentmods.dev/badge/skills/caipe-io/ai-platform-engineering/review-specific-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00055 | $0.01148 |
| Opus 5 | $0.00028 | $0.00574 |
| Sonnet 5 | $0.00011 | $0.00230 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
review-specific-pr 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review a Specific PR
Given a GitHub PR URL or identifier, perform a thorough code review covering correctness, security, performance, testing, and style.
Input
Requires a PR URL in the format `https://github.com/{owner}/{repo}/pull/{number}\` or `{owner}/{repo}#{number}`.
Instructions
Phase 1: Context Gathering
- Fetch PR metadata - title, description, author, branch, labels, linked issues
- Fetch the diff - all changed files with additions and deletions
- Fetch CI/CD status - check suite results, individual check runs
- Fetch existing reviews and comments - prior feedback from other reviewers
- Fetch linked issues - understand the intent behind the changes
Phase 2: Code Analysis
Analyze each changed file for:
-
Correctness & Logic
- Off-by-one errors, null/undefined handling, race conditions
- Proper error handling and edge cases
- Correct use of async/await patterns
- State management issues
-
Security
- Hardcoded credentials, API keys, tokens (NEVER allowed per project rules)
- SQL injection, XSS, CSRF vulnerabilities
- Insecure cryptographic algorithms (no MD5, SHA-1, DES, RC4)
- Proper input validation and sanitization
- Certificate handling (check expiration, key strength, signature algorithms)
-
Performance
- Unnecessary re-renders (React), N+1 queries, unbounded loops
- Memory leaks (event listeners, subscriptions not cleaned up)
- Missing pagination for large datasets (OOM protection)
- Expensive operations in hot paths
-
Testing
- Are new code paths covered by tests?
- Are edge cases tested?
- Do existing tests still pass?
- Integration test coverage for agent interactions
-
Style & Standards
- Conventional commit format in PR title
- DCO sign-off present in commits
- Python: Black formatting, Ruff compliance, type hints, Google-style docstrings
- TypeScript/React: Proper typing, component patterns
- Import organization (stdlib, third-party, local-package, local-relative)
What ships with it
1 file 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 · 130 lines · 55 tokens per session scan A 795faea42e42
review-specific-pr is a skill published in the GitHub repository caipe-io/ai-platform-engineering (408 stars, last pushed today), licensed Apache-2.0. It adds 55 tokens to every session and 1,148 once invoked, about $0.0003 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
codebase-sync
Convention discovery and rule generation from codebase analysis. Scans project structure, builds search indexes, identifies patterns, and generates enforceable rules.
code-review-patterns
Multi-dimensional code assessment across security, quality, performance, and maintainability with confidence-gated reporting (>=80%) and Router Contract generation.
code-review-pipeline
Multi-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.
plan-implementation
Disciplined execution of approved plans with step-by-step verification, phase checkpoints, failure investigation, and mandatory code/security reviews.
quality-checklist
Validate implementation quality through custom checklists, scoring against constitution standards, specification coverage, and producing remediation recommendations.
code-review
Multi-dimensional code review across correctness, security, performance, maintainability, and test coverage.