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review-fix

Review and fix critical and warning issues in changed Python files.

Updated Sep 9, 2024
Search Tags:#pytest#python#static-analysis#code-review#ci#automated-fixes#semantic-analysis
One-click install
npx skills add https://github.com/axel-kaliff/dotfiles --skill review-fix-axel-kaliff
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-fix
Source: https://github.com/axel-kaliff/dotfiles/tree/main/claude/.claude/skills/review-fix
Command: npx skills add https://github.com/axel-kaliff/dotfiles --skill review-fix-axel-kaliff

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the tedious, error-prone process of reviewing branch changes and applying concrete fixes for critical and warning issues so developers can ship safer code faster. It centralizes multiple analysis tools and reviewer personas into a repeatable pipeline that reduces false positives via semantic voting and enforces style and safety rules.

Core Features & Use Cases

  • Scope discovery: Collects changed, staged, and uncommitted Python files from the current branch and skips work when no targets exist.
  • Parallel analysis: Launches seven agents concurrently (static analysis, web confirmation, three semantic passes with voting, grumpy review, and style checks) and consolidates canonical findings.
  • Semantic voting & consolidation: Intersects multi-pass semantic reviewers to reduce false positives and deduplicates findings by file:line:source before building a prioritized fix list.
  • Safe automated fixes: Applies only listed, unambiguous edits via a dedicated fixer agent, marks ambiguous cases MANUAL, and avoids editing files outside the branch.
  • Test validation and reporting: Runs unit tests and diff-coverage, then produces a two-column report of applied fixes and manual items.
  • Disk-persisted mode: Supports batch or sequential disk-backed pipelines for large change sets to avoid context overflow.

Quick Start

Run the review-fix skill to analyze changed Python files in the current branch and apply safe automated fixes.

Frequently Asked Questions about review-fix

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

FAQPage Schema
How do I automatically fix Python code issues found in a git branch?▼

Automated Python code fixes work by collecting changed files from your git branch, running parallel static and semantic analyses, and applying unambiguous edits while marking complex cases for manual review.

How does semantic voting reduce false positives in automated code review?▼

Semantic voting reduces false positives in automated code review by running multiple analysis passes concurrently, intersecting the reviewer findings, and deduplicating results by file, line, and source before generating a prioritized fix list.

What do I need to run automated Python static analysis and fixes locally?▼

Running automated Python static analysis and fixes requires a git repository context, code editing capabilities, pytest for validation, and analysis tools like ruff, ty, and complexity checkers installed locally.

Can I review and fix a large Python change set without context overflow?▼

Yes, you can review and fix large Python change sets without context overflow by enabling the disk-persisted sequential mode, which batches the analysis pipeline to safely process extensive branch changes.

What happens to ambiguous code issues during automated Python code review?▼

During automated Python code review, ambiguous code issues are marked as MANUAL in the final report, ensuring the dedicated fixer agent only applies listed, unambiguous edits and avoids modifying files outside the branch.

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