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Command

/review-feedback

Review a given code review markdown document, GitHub PR review, or inline feedback — corroborate each point against actual code, then implement valid changes.

From plugin
spencermarx-open-code-review
36798 skills132 agents98 commands2 MCP
Install
> /plugin marketplace add spencermarx/open-code-review
> /plugin install ocr@aclarify

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/review-feedback

Context preview

What this command does when you run it.

Review a given code review markdown document, GitHub PR review, or inline feedback — corroborate each point against actual code, then implement valid changes.

Command definition

review-feedback.md
description: Review a given code review markdown document, GitHub PR review, or inline feedback — corroborate each point against actual code, then implement valid changes.

Review Feedback

Review a code review document, GitHub code review comment, or inline feedback. Corroborate each point against the actual implementation before acting.

Usage

After invoking, provide:

  • **REVIEW SOURCE** (one of the following):
  • A file path to a review markdown file (e.g., `.ocr/sessions/.../final.md`)
  • A GitHub PR link (e.g., `https://github.com/org/repo/pull/123`) pointing to a review or comment
  • Inline feedback pasted directly in the chat
  • **NOTES** *(optional)*: Any additional instructions, constraints, or priorities to keep front of mind while reviewing and implementing.

Guardrails

  • You are a distinguished software engineer with deep understanding of software architecture and design patterns.
  • Think step by step — favor composition, clear boundaries, minimal scope, and root-cause fixes.
  • Verify every assumption by reading actual code; never guess at behavior.
  • Adhere to existing patterns and project standards (`openspec/project.md`, `apps/dev-docs/docs/guides/coding-standards.md`).
  • Do NOT blindly accept every piece of feedback. Use your expertise to corroborate each point against the actual implementation before acting.
  • If feedback is incorrect or based on a misunderstanding of the code, say so clearly with evidence.
  • If feedback is valid but the suggested fix is suboptimal, propose a better alternative.
  • Direct cutover rewrites only — remove all deprecated/dead/unused code; leave nothing behind.

Steps

1. **Resolve Inputs**

  • **REVIEW SOURCE**: Determine the feedback source:

1. If the user provided a file path, read the file in its entirety to extract all review feedback. 2. If the user provided a GitHub PR link, use `gh pr view <number> --comments` or `gh api repos/{owner}/{repo}/pulls/{number}/comments` to fetch the review content. If the link points to a specific comment, focus on that comment; otherwise, gather all review comments. 3. If the user provided inline feedback directly, use it as-is. 4. If none of the above are provided or are ambiguous, stop and ask the user for clarification.

  • **NOTES**: Capture any additional user instructions. These take priority and should be kept front of mind throughout all subsequent steps.

2. **Parse and Catalog Feedback Items**

  • Break the review source into discrete, actionable feedback items.
  • For each item, record:
  • The feedback point (what the reviewer is saying)
  • The file(s) and line(s) referenced (if any)
  • Severity/type: bug, style, architecture, performance, naming, test coverage, etc.
  • Present a concise numbered summary of all feedback items to the user before proceeding.

3. **Gather Implementation Context**

  • Read ALL files referenced by the review feedback.
  • Read any additional files needed to understand the surrounding context (callers, consumers, types, tests).
  • Read `openspec/project.md` and `apps/dev-docs/docs/guides/coding-standards.md` if the feedback touches on standards or architecture.
  • **DO NOT skip any referenced files** — thorough context is critical for accurate corroboration.

4. **Corroborate and Validate Each Feedback Item** For each feedback item from Step 2:

  • **Read the actual code** at the referenced location.
  • **Assess validity**: Is the feedback accurate? Does the code actually exhibit the issue described?
  • **Classify** each item as one of:
  • **Valid — Will Address**: Feedback is correct and should be implemented.
  • **Valid — Alternative Approach**: Feedback identifies a real issue but the suggested fix is suboptimal; propose a better solution.
  • **Invalid — Respectfully Decline**: Feedback is based on a misunderstanding or is incorrect; explain why with code evidence.
  • **Needs Clarification**: Feedback is ambiguous or requires more context to evaluate.
  • Present the corroboration results to the user as a summary table or list before implementing. Wait for user acknowledgment.

5. **Address Feedback** For all items classified as **Valid — Will Address** or **Valid — Alternative Approach**:

  • Implement changes following project coding standards and existing patterns.
  • Apply any user-provided NOTES as additional constraints.
  • Group related changes logically (e.g., all changes to one file together).
  • For **Alternative Approach** items, implement the better solution you proposed in Step 4.
  • Ensure every change is minimal, focused, and does not introduce regressions.
  • Run any relevant linting or type-checking commands to verify correctness.

6. **Report Completion** Summarize:

  • Total feedback items reviewed
  • Items addressed (with brief description of each change)
  • Items declined (with reasoning)
  • Items needing clarification (if any)
  • Any remaining follow-up actions or open questions

Output

The workflow produces: 1. A numbered catalog of all feedback items with corroboration status 2. Implemented code changes for all valid feedback 3. A completion summary with change descriptions, declined items with reasoning, and any open questions

Read more
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AI-powered multi-agent code review. Simulates a customizable team of Engineers performing code review with built-in discourse.

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