Vibe-Skills is a collection and routing system that helps AI agents discover, select, and coordinate specialized skills for completing tasks. It is intended for agents that need to organize workflows across many installed capabilities. The catalogue entries are skills and an agent belonging to this system.
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 foryourhealth111-pixel/Vibe-Skills --skill receiving-code-reviewgit clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-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/foryourhealth111-pixel/vibe-skills/receiving-code-review)<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/receiving-code-review"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/receiving-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/foryourhealth111-pixel/vibe-skills/receiving-code-review"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/receiving-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 | $0.00052 | $0.01552 |
| Opus 5 | $0.00026 | $0.00776 |
| Sonnet 5 | $0.00010 | $0.00310 |
| Haiku 4.5 | $0.00005 | $0.00155 |
Grade A, and why
receiving-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 9d 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
81% identical to receiving-code-review — 18 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 — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Reception
Overview
Code review requires technical evaluation, not emotional performance.
Core principle: Verify before implementing. Ask before assuming. Technical correctness over social comfort.
Routing Boundary
Use this skill only when feedback already exists and must be evaluated. A fresh request like "review this PR" belongs to code-reviewer; a request like "run OWASP security audit" belongs to security-reviewer.
The Response Pattern
WHEN receiving code review feedback:
1. READ: Complete feedback without reacting
2. UNDERSTAND: Restate requirement in own words (or ask)
3. VERIFY: Check against codebase reality
4. EVALUATE: Technically sound for THIS codebase?
5. RESPOND: Technical acknowledgment or reasoned pushback
6. IMPLEMENT: One item at a time, test each
Forbidden Responses
NEVER:
- "You're absolutely right!" (explicit CLAUDE.md violation)
- "Great point!" / "Excellent feedback!" (performative)
- "Let me implement that now" (before verification)
INSTEAD:
- Restate the technical requirement
- Ask clarifying questions
- Push back with technical reasoning if wrong
- Just start working (actions > words)
Handling Unclear Feedback
IF any item is unclear:
STOP - do not implement anything yet
ASK for clarification on unclear items
WHY: Items may be related. Partial understanding = wrong implementation.
Example:
your human partner: "Fix 1-6"
You understand 1,2,3,6. Unclear on 4,5.
❌ WRONG: Implement 1,2,3,6 now, ask about 4,5 later
✅ RIGHT: "I understand items 1,2,3,6. Need clarification on 4 and 5 before proceeding."
Source-Specific Handling
From your human partner
- Trusted - implement after understanding
- Still ask if scope unclear
- No performative agreement
- Skip to action or technical acknowledgment
From External Reviewers
BEFORE implementing:
1. Check: Technically correct for THIS codebase?
2. Check: Breaks existing functionality?
3. Check: Reason for current implementation?
4. Check: Works on all platforms/versions?
5. Check: Does reviewer understand full context?
IF suggestion seems wrong:
Push back with technical reasoning
IF can't easily verify:
Say so: "I can't verify this without [X]. Should I [investigate/ask/proceed]?"
IF conflicts with your human partner's prior decisions:
Stop and discuss with your human partner first
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.
- 9d ago First seen · 218 lines · 52 tokens per session scan A 86be4ebbbb53
receiving-code-review is a skill published in the GitHub repository foryourhealth111-pixel/Vibe-Skills (3,252 stars, last pushed 12d ago), licensed Apache-2.0. It adds 52 tokens to every session and 1,552 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to receiving-code-review, differing in 18 lines, and is treated as a copy.
Other skills, from other repositories
meta-reviewing-ai-reviewing
AI integration review patterns. Use when reviewing model API calls, prompt construction, LLM output handling, RAG pipelines, and tool-calling code. Covers prompt-injection call-chain tracing, output validation, token budgets, retry/timeout handling, streaming, and key/PII exposure.
meta-reviewing-api-reviewing
Backend code review patterns. Use when reviewing API routes, database operations, auth middleware, and server utilities. Covers injection, boundary validation, authorization coverage, secret/PII exposure, error leakage, and query patterns.
meta-reviewing-cli-reviewing
CLI code review patterns. Use when reviewing CLI applications built with Commander.js, @clack/prompts, picocolors. Covers exit codes, signal handling, error messages, user experience, testing adequacy.
meta-reviewing-infra-reviewing
Infrastructure code review patterns. Use when reviewing CI/CD workflows, Dockerfiles, deployment configs, and IaC. Covers supply-chain pinning, secret exposure, container hygiene, least-privilege permissions, and deployment safety.
meta-reviewing-web-reviewing
UI component review patterns. Use when reviewing React components, hooks, props, state, styling, and accessibility. Covers rules of hooks, effect cleanup, render performance, list keys, keyboard and ARIA patterns.
meta-reviewing-reviewing
Code review patterns, feedback principles. Use when reviewing PRs, implementations, or making approval/rejection decisions. Covers self-correction, progress tracking, feedback principles, severity levels.