Borrowing it
Nothing to install: this file belongs to PageAI-Pro/ralph-loop. 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/PageAI-Pro/ralph-loop/main/.agent/skills/frontend-code-review/SKILL.mdgit clone --depth 1 https://github.com/PageAI-Pro/ralph-loopWrote 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/pageai-pro/ralph-loop/frontend-code-review)<a href="https://agentmods.dev/skills/pageai-pro/ralph-loop/frontend-code-review"><img src="https://agentmods.dev/badge/skills/pageai-pro/ralph-loop/frontend-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/pageai-pro/ralph-loop/frontend-code-review"><img src="https://agentmods.dev/badge/skills/pageai-pro/ralph-loop/frontend-code-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 | $0.00042 | $0.00597 |
| Opus 5.5 | $0.00017 | $0.00239 |
| Sonnet 5.5 | $0.00008 | $0.00119 |
| Haiku 4.5 | $0.00004 | $0.00060 |
Grade A, and why
frontend-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 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.
This is a copy
92% identical to frontend-code-review — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Frontend Code Review
Intent
Use this skill whenever the user asks to review frontend code (especially .tsx, .ts, or .js files). Support two review modes:
- Pending-change review – inspect staged/working-tree files slated for commit and flag checklist violations before submission.
- File-targeted review – review the specific file(s) the user names and report the relevant checklist findings.
Stick to the checklist below for every applicable file and mode.
Checklist
See references/code-quality.md, references/performance.md, for the living checklist split by category—treat it as the canonical set of rules to follow.
Flag each rule violation with urgency metadata so future reviewers can prioritize fixes.
Review Process
- Open the relevant component/module. Gather lines that relate to class names, React Flow hooks, prop memoization, and styling.
- For each rule in the review point, note where the code deviates and capture a representative snippet.
- Compose the review section per the template below. Group violations first by Urgent flag, then by category order (Code Quality, Performance, Business Logic).
Required output
When invoked, the response must exactly follow one of the two templates:
Template A (any findings)
# Code review
Found <N> urgent issues need to be fixed:
## 1 <brief description of bug>
FilePath: <path> line <line>
<relevant code snippet or pointer>
### Suggested fix
<brief description of suggested fix>
---
... (repeat for each urgent issue) ...
Found <M> suggestions for improvement:
## 1 <brief description of suggestion>
FilePath: <path> line <line>
<relevant code snippet or pointer>
### Suggested fix
<brief description of suggested fix>
---
... (repeat for each suggestion) ...
If there are no urgent issues, omit that section. If there are no suggestions, omit that section.
If the issue number is more than 10, summarize as "10+ urgent issues" or "10+ suggestions" and just output the first 10 issues.
What ships with it
2 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.
- 1mo ago First seen · 74 lines · 42 tokens per session scan A d4336ed7a6fe
frontend-code-review is a skill published in the GitHub repository PageAI-Pro/ralph-loop (328 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 597 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to frontend-code-review, differing in 2 lines, and is treated as a copy.
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