followup-cleanup

Prune false positives and add stale-data warnings to review plans.

1|Updated Jan 12, 2026
One-click install
npx skills add https://github.com/cwilliams5/Alt-Tabby --skill followup-cleanup
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: followup-cleanup
Source: https://github.com/cwilliams5/Alt-Tabby/tree/main/.claude/skills/followup-cleanup
Command: npx skills add https://github.com/cwilliams5/Alt-Tabby --skill followup-cleanup

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill streamlines review plans by removing irrelevant items and adding crucial warnings, ensuring coding agents can efficiently and accurately implement feedback.

Core Features & Use Cases

  • Prunes False Positives: Removes items validated as non-issues or by-design, preventing wasted effort.
  • Adds Stale-Data Warnings: Alerts the coding agent to verify line numbers and code context due to potential repository changes.
  • Use Case: After a code review, this Skill prepares the identified issues into a clean, actionable list for a developer, complete with a reminder to double-check line numbers before making changes.

Quick Start

Prepare the current review plan for handoff to a coding agent by removing false positives and adding stale-data warnings.

Frequently Asked Questions about followup-cleanup

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

FAQPage Schema
How do I prepare a code review plan for developer handoff to a coding agent?

Preparing a code review plan for developer handoff involves pruning validated false positives and adding stale-data warnings to ensure the coding agent receives a clean, actionable list. This refinement mitigates risks of incorrect implementation by flagging potential repository changes.

What is the best way to remove false positives from a coding agent review plan?

The best way to remove false positives from a review plan is to prune items validated as non-issues or by-design. This prevents wasted effort and ensures the coding agent only processes relevant, actionable feedback before implementation.

Why does my coding agent implement changes on incorrect line numbers after a repository update?

Coding agents implement changes on incorrect line numbers because of stale data caused by repository updates. Adding explicit stale-data warnings to the review plan alerts the agent to verify line numbers and code context before making modifications.

Can I refine a review plan to mitigate risks of incorrect implementation by a coding agent?

Yes, you can refine a review plan to mitigate incorrect implementation risks by removing irrelevant items and adding crucial warnings. This ensures actionable items are presented clearly, preventing wasted effort on outdated code context.

When do I need to add stale-data warnings to a code review plan?

You need to add stale-data warnings to a code review plan whenever potential repository changes might shift line numbers or code context. This alerts the coding agent to double-check the environment before executing the refined handoff.