Borrowing it
Nothing to install: this file belongs to AmanKtyr/Tailor. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AmanKtyr/Tailor/main/.agents/skills/review/SKILL.mdgit clone --depth 1 https://github.com/AmanKtyr/TailorWrote 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/amanktyr/tailor/review)<a href="https://agentmods.dev/skills/amanktyr/tailor/review"><img src="https://agentmods.dev/badge/skills/amanktyr/tailor/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/amanktyr/tailor/review"><img src="https://agentmods.dev/badge/skills/amanktyr/tailor/review.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 | $0.00030 | $0.00469 |
| Opus 5.5 | $0.00012 | $0.00188 |
| Sonnet 5.5 | $0.00006 | $0.00094 |
| Haiku 4.5 | $0.00003 | $0.00047 |
Grade A, and why
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 1mo 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code & Architecture Review Skill
Activate this skill when reviewing code changes, evaluating pull requests, or conducting a project-wide health review (/review or tailor review).
Review Directive: Provide actionable, prioritized feedback focusing on architecture, security, code reuse, and long-term maintainability.
1. Multi-Dimensional Review Rubric
Evaluate code changes across 5 core dimensions:
- Architecture & Boundaries: Does the implementation violate established ADRs in
.ai/DECISIONS.mdor cross layer boundaries illegally? - Reuse & Duplication: Could this code have reused existing components, utilities, or abstractions instead of introducing duplicates?
- Dependency Governance: Were unnecessary external packages added when standard library primitives or native APIs suffice?
- Security & Validation: Are user inputs sanitized? Are database queries parameterized? Are secrets kept out of source code?
- Testing & Quality: Are there targeted tests covering happy paths, error handling, and edge cases?
2. Standardized Actionable Finding Schema
Structure all review feedback using this concise format:
### [SEVERITY] REV-00X: [Clear Issue Summary]
- **Severity Level:** CRITICAL | HIGH | MEDIUM | LOW | INFO
- **File Location:** `src/features/auth/login.ts:28`
- **Problem Statement:** Concise explanation of the flaw or anti-pattern.
- **Impact & Risk:** Why this matters (security compromise, memory leak, code duplication).
- **Remediation Code:**
```ts
// Replace the insecure/duplicate block with this implementation
---
## 3. Pull Request Review Checklist
- [ ] Zero unvalidated user inputs reaching database or shell execution.
- [ ] Zero hardcoded credentials, API keys, or JWT secrets.
- [ ] Existing UI components and helpers reused where applicable.
- [ ] No new micro-packages introduced without justification.
- [ ] All automated tests pass with exit code 0.
- [ ] Updated project memory documentation in `.ai/` if architecture or schemas changed.
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.
- 1mo ago First seen · 52 lines · 30 tokens per session scan A c4fb9c568782
review is a skill published in the GitHub repository AmanKtyr/Tailor (6 stars, last pushed 11d ago), licensed MIT. It adds 30 tokens to every session and 469 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
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