index-repo-py

Generate a compact PROJECT_INDEX.md for Python FastAPI projects.

Updated Dec 22, 2025

Search Tags:#documentation #indexing #fastapi #python #code-navigation #project-index

Ready to run

npx skills add https://github.com/senior-sigan/llm-skills --skill index-repo-py

💬 Prompt for ChatGPT / Claude Chat▼

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.