index-repo-py

Generate a compact PROJECT_INDEX.md for Python FastAPI projects.

Updated Dec 22, 2025
One-click install
npx skills add https://github.com/senior-sigan/llm-skills --skill index-repo-py
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: index-repo-py
Source: https://github.com/senior-sigan/llm-skills/tree/main/skills/index-repo-py
Command: npx skills add https://github.com/senior-sigan/llm-skills --skill index-repo-py

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Large Python FastAPI repositories are hard to navigate and understand quickly. This Skill generates a compact, human-friendly PROJECT_INDEX.md that summarizes the codebase by extracting purpose, public exports, endpoints, and test fixtures, enabling rapid orientation without reading every file.

Core Features & Use Cases

  • Automated indexing: scans source and test files to build a concise index.
  • Export discovery: lists public classes, functions, and constants available to users.
  • Size-conscious output: keeps PROJECT_INDEX.md within a small footprint for fast load times.
  • Use Case: a developer onboarding a large FastAPI project can skim the index to locate relevant modules and endpoints without reading through the entire repository.

Quick Start

Run the skill to generate PROJECT_INDEX.md for the current Python FastAPI project.

Frequently Asked Questions about index-repo-py

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

FAQPage Schema
How do I generate a Python FastAPI project index for code navigation?

To generate a Python FastAPI project index, run the skill to scan source and test files, extract purposes and endpoints, and write a structured PROJECT_INDEX.md for fast codebase navigation.

What is a compact PROJECT_INDEX.md and how does it help with FastAPI codebases?

A compact PROJECT_INDEX.md is a human-friendly summary file that extracts public exports, endpoints, and test fixtures from a large FastAPI codebase, enabling rapid orientation without reading every file.

Does this project indexing approach work with both source and test files?

Yes, project indexing with this approach works with both source and test files by globbing the repository, parsing each file for metadata, and extracting public exports alongside test fixtures.

How do I keep my FastAPI project documentation within a small size limit?

Keep FastAPI project documentation within a small size limit by using this deterministic workflow, which enforces a target size constraint on the generated PROJECT_INDEX.md for fast load times.

Can I discover FastAPI endpoints and public exports automatically across a repository?

Yes, you can discover FastAPI endpoints and public exports automatically by running this skill, which parses each file to extract public classes, functions, constants, and API endpoints into a concise index.

What are the limitations of automated codebase indexing for Python projects?

The limitation of this automated codebase indexing is that it is specifically applicable to source-heavy Python FastAPI projects, and its deterministic parsing may not capture non-standard or dynamically generated module structures.