cartographer

Analyze pull request diffs and group code changes into semantic feature clusters.

2|Updated Mar 16, 2026
One-click install
npx skills add https://github.com/hamzaPixl/pixl-ai --skill cartographer-hamzapixl
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cartographer
Source: https://github.com/hamzaPixl/pixl-ai/tree/main/packages/crew/skills/cartographer
Command: npx skills add https://github.com/hamzaPixl/pixl-ai --skill cartographer-hamzapixl

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The cartographer skill transforms raw pull‑request and local repository changes into clear, intent‑driven feature clusters, making code reviews, churn analysis, and impact explanations straightforward.

Core Features & Use Cases

  • Semantic clustering: Groups committed and uncommitted changes by purpose rather than file paths.
  • Churn quantification: Calculates line‑additions and deletions per feature, including cross‑cutting work.
  • Artifact generation: Produces a comprehensive CARTOGRAPH.MD report with motivations, implementations, dependencies, and verification checks.
  • Use case: Ideal for engineers preparing PR reviews, team leads assessing development impact, or CI pipelines summarizing change intent.

Quick Start

Run the cartographer skill on your PR branch to produce a detailed CARTOGRAPH.MD report summarizing feature clusters and churn.

Frequently Asked Questions about cartographer

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

FAQPage Schema
How do I group pull request diffs into semantic feature clusters?

To group pull request diffs into semantic feature clusters, use the cartographer skill on your Git repository to decompose changes by purpose. It generates a markdown artifact detailing per-feature motivations, dependencies, and balanced line-count verification.

Can I quantify code churn per feature across committed and uncommitted changes?

Yes, you can quantify code churn per feature by analyzing local and committed changes. The skill calculates line additions and deletions for each semantic feature cluster, including cross-cutting work, and outputs the metrics in a markdown report.

What is the best way to generate a markdown summary of code changes for PR review?

The best way to generate a markdown summary for PR review is to run the cartographer skill on your PR branch. It produces a CARTOGRAPH.MD report that explains implementation impact and summarizes feature clusters for straightforward review.

Does the cartographer skill require external dependencies to analyze Git repositories?

No, the cartographer skill does not require external dependencies to analyze Git repositories. It operates independently to evaluate local and committed changes, grouping them into intent-driven feature clusters for churn quantification and impact explanation.

How does feature clustering handle cross-cutting code changes in a pull request?

Feature clustering handles cross-cutting code changes by grouping them semantically rather than by file paths. It calculates line additions and deletions for each feature, ensuring that shared modifications are quantified and reported in the markdown artifact.

When should I not use automated feature clustering for pull request analysis?

You should avoid automated feature clustering when you only need raw file-level diff outputs rather than intent-driven semantic groupings. The skill is designed for engineers needing per-feature churn metrics, motivations, and impact explanations.