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receiving-code-review

Validate code review feedback against the project's code graph and analytical database.

2|Updated Apr 15, 2026
Search Tags:#code review#pull request#refactoring#verification#technical rigor#code graph
One-click install
npx skills add https://github.com/getspur/spur --skill receiving-code-review-getspur
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: receiving-code-review
Source: https://github.com/getspur/spur/tree/main/.spur/skills/receiving-code-review
Command: npx skills add https://github.com/getspur/spur --skill receiving-code-review-getspur

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill prevents performative agreement and blind implementation of code review feedback by grounding responses in objective evidence from the code graph.

Core Features & Use Cases

  • Evidence-Based Verification: Uses code graph tools to validate reviewer claims about dead code, performance, or architectural impact.
  • Structured Pushback: Provides a framework for technically sound disagreement when reviewer suggestions are incorrect or out of scope.
  • Use Case: When a reviewer claims a function is unused, use this skill to query the code graph for callers and provide the exact count as evidence before deciding whether to remove it.

Quick Start

Use the receiving-code-review skill to verify the reviewer's claim that the current function is unused by running the appropriate graph query.

Frequently Asked Questions about receiving-code-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate code review feedback before implementing changes?▼

To validate code review feedback, cross-reference reviewer claims against the project's code graph. Query the analytical database to find quantitative evidence for implementation decisions before modifying a pull request.

How do I verify if a function is dead code when a reviewer says it is unused?▼

Verify dead code claims by querying the code graph for callers of the function. This provides an exact caller count as evidence to confirm whether the reviewer's suggestion to remove it is technically accurate.

How do I push back on incorrect pull request review comments?▼

Push back on incorrect review comments using structured disagreement grounded in objective evidence. Apply technical rigor to validate architectural impact claims before rejecting out-of-scope or inaccurate reviewer suggestions.

When do I need to cross-reference code review suggestions with a code graph?▼

Cross-reference code review suggestions with a code graph when maintaining architectural integrity against external feedback. This prevents performative agreement by validating claims about performance, dead code, or structural impact.

Do I need code-explore and spur-analyst tools to verify reviewer claims?▼

Yes, verifying reviewer claims requires integration with code-explore and spur-analyst tools. These dependencies query the code graph to supply the quantitative evidence needed for all implementation decisions.

What is the best way to handle code review feedback that seems out of scope?▼

Handle out-of-scope code review feedback by cross-referencing the claims against the analytical database. Evidence-based verification confirms whether suggestions align with the project's architecture before implementation.

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