corpis 0.1.2

Codebase knowledge layer for AI coding agents

Corpis

A codebase knowledge layer for AI coding agents. Corpis analyses every source file in your project, distils each one into a structured logic record (purpose, mechanics, decision history), and makes the whole thing queryable in plain English.

Every AI agent working in your repo — Claude, Gemini, GPT — can query Corpis before reading source files, getting instant grounded answers without burning context.

Install

pip install corpis

Quickstart

cd my-project
corpis init        # scaffold corpis/, create .env, write agent instruction files
# add your OPENAI_API_KEY to corpis/.env
corpis genesis     # ingest the codebase (run once)
corpis query       # start asking questions

Commands

Command	Description
corpis init	Scaffold Corpis in the current project
corpis genesis [--reset]	Ingest all source files into the knowledge corpus
corpis query	Interactive TUI chat interface (or pipe: echo "question" | corpis query)
corpis update <file> "<why>"	Update a file's record after a code change
corpis delete <file>	Remove a file's record from the corpus
corpis cache	Browse the semantic answer cache

How it works

1. Genesis — walks your repo, sends each file to GPT-4o, and writes a structured logic record: what the code does, why it exists, and how it works. Records are stored in corpis/docs/ organised by business domain.

2. Query — two-stage agentic retrieval: scout (semantic search across all records) → AI selects the most relevant ones → synthesise a grounded answer. Answers are cached semantically so identical or paraphrased questions return instantly.

3. Update — after every code change, run corpis update <file> "<why>". The record gets a new dated changelog entry and any stale cached answers are invalidated automatically.

Agent integration

corpis init writes instruction files for every major AI coding agent:

• CLAUDE.md — imperative instructions for Claude Code
• AGENTS.md — instructions for OpenAI Codex / GPT agents
• GEMINI.md — instructions for Gemini CLI

Agents are instructed to query Corpis before reading source files and to run corpis update after every change — keeping the knowledge corpus current without any manual effort.

Requirements

• Python 3.9+
• OpenAI API key (used for embeddings and synthesis)