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respond-review

Parse hachimoku JSONL review output into accept or reject response plans.

1|1|Updated Jan 16, 2026
Search Tags:#automation#code review#github#pull requests#review feedback#jsonl#hachimoku
One-click install
npx skills add https://github.com/drillan/mixseek-plus --skill respond-review
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: respond-review
Source: https://github.com/drillan/mixseek-plus/tree/main/.claude/skills/respond-review
Command: npx skills add https://github.com/drillan/mixseek-plus --skill respond-review

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you read hachimoku review output and turn scattered reviewer comments into a structured response workflow, so you can act on feedback quickly and consistently.

Core Features & Use Cases

  • Loads the latest review JSONL for a PR or diff run and extracts all successful agent issues.
  • Sorts findings by severity, presents a decision table, and guides accept or reject handling.
  • Supports updating files and committing the resulting fixes after accepted feedback is implemented.
  • Use it when you need to triage multi-agent code review feedback, resolve actionable issues, and document why certain suggestions were skipped.

Quick Start

Ask the skill to process the current review feedback for a specific pull request or the diff run and help you decide which comments to accept or reject.

Frequently Asked Questions about respond-review

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

FAQPage Schema
How do I turn GitHub pull request review feedback into actionable fixes?▼

To turn pull request review feedback into actionable fixes, parse the hachimoku JSONL output to extract issues, sort them by severity, and generate a structured response plan with accept or reject decisions.

How do I aggregate multi-agent code review findings from a diff session?▼

Aggregating multi-agent code review findings requires loading the latest review JSONL, extracting successful agent issues, and sorting them by severity to produce a unified decision table for remediation tracking.

Can I automatically commit file fixes after accepting code review suggestions?▼

Yes, after accepting review suggestions, you can update the affected files and create a commit directly within the structured response workflow to finalize the remediation tracking.

What is the best way to triage hachimoku review comments by severity?▼

The best way to triage hachimoku review comments is to parse the JSONL output, extract the issue metadata, and sort the findings by severity to guide your accept or reject decisions.

How does the code review response workflow handle agent errors in JSONL output?▼

The response workflow handles agent errors by reading the latest review session, filtering out failed agents, and extracting only the successful agent issues to ensure clean issue aggregation.

Do I need a specific file format to document rejected code review suggestions?▼

You need the hachimoku JSONL file format to load review sessions, extract issue metadata, and document your structured response plan with explicit accept or reject decisions for skipped suggestions.

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