code-mapper-skill

Name: code-mapper-skill
Availability: InStock
Author: dachent

Generate deterministic Python import, reference, artifact, contract, and CodeQL maps for static repository analysis.

18|1|Updated Mar 19, 2026

Search Tags:#python #code-analysis #dependency-mapping #codeql #ast #api-contracts

Ready to run

npx skills add https://github.com/dachent/skills --skill code-mapper-skill

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-mapper-skill
Source: https://github.com/dachent/skills/tree/main/code-mapper-skill
Command: npx skills add https://github.com/dachent/skills --skill code-mapper-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires grimp, jedi, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill solves the problem of understanding complex, large-scale Python repository structures, dependencies, and contract relationships without manually exploring files or executing untrusted code.

Core Features & Use Cases

Blast Radius Analysis: Identify transitive dependencies and import cycles to understand the impact of code changes.
Contract & Lineage Mapping: Extract API endpoints, schemas, and Backstage catalog relationships from OpenAPI, GraphQL, Protobuf, and other contract files.
Semantic Enrichment: Optionally leverage CodeQL for targeted local value and taint flow analysis to identify how data moves through your application.

Quick Start

Run the code-mapper-skill to generate a comprehensive JSON dependency and contract map for the current repository by pointing it at your local project root.

Frequently Asked Questions about code-mapper-skill

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

FAQPage Schema

How do I map Python import dependencies and reference cycles in a large repository?▼

To map Python import dependencies and reference cycles, this Skill uses grimp and jedi to generate deterministic JSON maps of transitive dependencies for static repository analysis. It identifies blast radius and cyclical imports without executing untrusted code.

How does CodeQL taint flow analysis work for Python codebases?▼

CodeQL taint flow analysis for Python codebases optionally provides semantic enrichment by tracking local value and data movement through your application. It generates targeted evidence of how data flows, complementing the base dependency and contract maps.

What is the best way to extract API contracts from OpenAPI, GraphQL, and Protobuf files?▼

The best way to extract API contracts from OpenAPI, GraphQL, and Protobuf files is using this Skill's contract and lineage mapping feature. It parses schemas and Backstage catalog relationships to generate deterministic artifact maps.

Do I need to configure a specific work root for Python static code analysis?▼

Yes, you must configure an explicit work root for Python static code analysis. The Skill adheres to strict read-only preflight policies for safety, requiring a local project root directory to generate dependency and contract maps.

Can I use grimp and jedi for blast radius analysis without running untrusted code?▼

Yes, you can use grimp and jedi for blast radius analysis without running untrusted code. This Skill performs static repository analysis to identify transitive dependencies and import cycles safely under strict read-only policies.

What are the limitations of static dependency mapping for Python projects?▼

Limitations of static dependency mapping include requiring an explicit work root configuration and adhering to strict read-only preflight policies. CodeQL semantic enrichment is optional and focused on local value flow rather than full runtime analysis.