LQF_Machine_Learning_E…
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
Review-feedback handling route for CodeRabbit, GitHub, PR, or human reviewer comments. Use before implementing suggestions to verify each finding. Do not use for a fresh code review, security audit, TDD, or final completion evidence.
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill receiving-code-review --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/receiving-code-reviewContext preview
The summary Claude sees to decide when to auto-load this skill.
Review-feedback handling route for CodeRabbit, GitHub, PR, or human reviewer comments. Use before implementing suggestions to verify each finding. Do not use for a fresh code review, security audit, TDD, or final completion evidence.
name: receiving-code-review description: Review-feedback handling route for CodeRabbit, GitHub, PR, or human reviewer comments. Use before implementing suggestions to verify each finding. Do not use for a fresh code review, security audit, TDD, or final completion evidence.
Code review requires technical evaluation, not emotional performance.
**Core principle:** Verify before implementing. Ask before assuming. Technical correctness over social comfort.
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`.
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
**NEVER:**
**INSTEAD:**
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."
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
**your human partner's rule:** "External feedback - be skeptical, but check carefully"
IF reviewer suggests "implementing properly": grep codebase for actual usage IF unused: "This endpoint isn't called. Remove it (YAGNI)?" IF used: Then implement properly
**your human partner's rule:** "You and reviewer both report to me. If we don't need this feature, don't add it."
FOR multi-item feedback:
1. Clarify anything unclear FIRST
2. Then implement in this order:
- Blocking issues (breaks, security)
- Simple fixes (typos, imports)
- Complex fixes (refactoring, logic)
3. Test each fix individually
4. Verify no regressionsPush back when:
**How to push back:**
**Signal if uncomfortable pushing back out loud:** "Strange things are afoot at the Circle K"
When feedback IS correct:
✅ "Fixed. [Brief description of what changed]" ✅ "Good catch - [specific issue]. Fixed in [location]." ✅ [Just fix it and show in the code] ❌ "You're absolutely right!" ❌ "Great point!" ❌ "Thanks for catching that!" ❌ "Thanks for [anything]" ❌ ANY gratitude expression
**Why no thanks:** Actions speak. Just fix it. The code itself shows you heard the feedback.
**If you catch yourself about to write "Thanks":** DELETE IT. State the fix instead.
If you pushed back and were wrong:
✅ "You were right - I checked [X] and it does [Y]. Implementing now." ✅ "Verified this and you're correct. My initial understanding was wrong because [reason]. Fixing." ❌ Long apology ❌ Defending why you pushed back ❌ Over-explaining
State the correction factually and move on.
| Mistake | Fix | |---------|-----| | Performative agreement | State requirement or just act | | Blind implementation | Verify against codebase first | | Batch without testing | One at a time, test each | | Assuming reviewer is right | Check if breaks things | | Avoiding pushback | Technical correctness > comfort | | Partial implementation | Clarify all items first | | Can't verify, proceed anyway | State limitation, ask for direction |
**Performative Agreement (Bad):**
Reviewer: "Remove legacy code" ❌ "You're absolutely right! Let me remove that..."
**Technical Verification (Good):**
Reviewer: "Remove legacy code" ✅ "Checking... build target is 10.15+, this API needs 13+. Need legacy for backward compat. Current impl has wrong bundle ID - fix it or drop pre-13 support?"
**YAGNI (Good):**
Reviewer: "Implement proper metrics tracking with database, date filters, CSV export" ✅ "Grepped codebase - nothing calls this endpoint. Remove it (YAGNI)? Or is there usage I'm missing?"
**Unclear Item (Good):**
your human partner: "Fix ite
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Repo: foryourhealth111-pixel/Vibe-Skills
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
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