recipro-ai 0.1.0

Autonomous multi-agent code improvement system

Recipro

Autonomous multi-agent code improvement. Point it at a repo, tell it what to do, and it plans, implements, reviews, and ships a PR — no manual intervention.

Install

pip install recipro-ai

Prerequisites

• Python 3.11+
• claude CLI — npm install -g @anthropic-ai/claude-code then claude login
• codex CLI — npm install -g @openai/codex then codex login (if using Codex as builder/critic)
• git and gh (GitHub CLI, for PR creation)
• OPENAI_API_KEY or GEMINI_API_KEY env var (optional, for ambient supervisor)

Quick start

recipro

On first run, Recipro walks you through setup:

First-time setup:
  Target repo path: /path/to/your/repo
  Planner model: ...
  Critic backend: ...
  Builder backend: ...
  Ambient narrator: ...
  Preferences saved to ~/.recipro/.

What should Recipro focus on?
  > your directive here (or press Enter for general scan)

Preferences persist — subsequent runs only ask for the focus directive.

Usage

recipro                          # Run: setup (if first time) → focus → execute
recipro --reconfigure            # Re-do setup (change repo, backends, models)
recipro --set KEY=VALUE          # Change a config setting
recipro --dry-run                # Plan only, no repo changes
recipro --clean                  # Reset dirty worktree from a failed run

Focus directive

Each run asks what Recipro should focus on. You can write in any language:

What should Recipro focus on?
  > Add input validation to all API endpoints

Press Enter with no input for a general code scan (finds bugs, security issues, maintainability improvements).

Changing settings

Backend, model, and repo path — re-run interactive setup:

recipro --reconfigure

Config toggles — set directly from CLI:

recipro --set verbose=true           # Show raw agent output
recipro --set max_improvements=3     # Tasks per run
recipro --set auto_merge=true        # Squash-merge PRs automatically
recipro --set require_clean_worktree=false

Cleaning up

If a run fails and leaves the target repo in a dirty state:

recipro --clean

This discards uncommitted changes, switches back to main, and deletes all recipro/* task branches.

How it works

┌─────────┐     ┌─────────┐     ┌─────────┐       ┌─────────┐     ┌─────────┐
│ Planner │ ──▶ │ Builder │ ──▶ │ Critic  │ ──▶   │ Builder │ ──▶ │ Builder │
│ (Claude)│     │         │     │         │       │ Verify  │     │ Push PR │
│ Scan &  │     │ Implement│    │ Review  │       │ Lint &  │     │ Branch, │
│ plan    │     │ changes │  ◀──│ findings│  ◀──  │ test    │     │ commit, │
│ tasks   │     │         │     │         │       │         │     │ push    │
└─────────┘     └────┬────┘     └─────────┘       └────┬────┘     └─────────┘
                     │              │   │              │
                     └──── loop ────┘   │ fix failures │
                                        └──────────────┘
                                         ┌──────────┐
                  Observing all of ───▶  │ Ambient  │
                  the above              │ Agent    │
                                         │ (GPT/    │
                                         │ Gemini)  │
                                         └──────────┘

1. Planner (Claude) — scans the repo and breaks the directive into concrete tasks
2. Builder (Claude or Codex) — implements each task
3. Critic (Claude or Codex) — reviews changes, sends findings back to Builder (loops until pass)
4. Builder — runs lint and tests; if anything fails, fixes and re-runs (loops until pass)
5. Builder — creates branch, commits, pushes, opens PR
6. Ambient Agent (GPT or Gemini) — monitors all agent output in the background, provides status updates, cost tracking, and anomaly detection

Features

• Mix and match backends — assign Claude or Codex independently to each role (planner/builder/critic)
• Focus mode — natural-language directive each run, any language. No directive = general scan
• Ambient supervisor — background agent watching all output, reporting status, catching stuck loops, estimating costs
• Automatic PR creation — full git workflow: pull latest, branch, lint, test, commit, push, PR
• Auto-merge — optionally squash-merge PRs after creation
• Worktree cleanup — --clean resets a dirty repo left by a failed run
• Zero dependencies — pure Python stdlib

Configuration

~/.recipro/config.yaml (auto-created on first run, editable via recipro --set):

max_improvements: 1            # Tasks per run
require_clean_worktree: true   # Require clean git state before run
auto_merge: false              # Auto squash-merge PRs after creation
verbose: false                 # Show raw agent streaming output

Backend/model selections are in ~/.recipro/memory/preferences.json, managed via recipro --reconfigure.

Data directory

~/.recipro/
├─ config.yaml             # Settings
├─ memory/
│  ├─ preferences.json     # Repo path, backend/model selections
│  └─ state.json           # Run history
└─ reports/                # Per-run operational reports

Notes

• Recipro pulls the latest code (git pull) before each run.
• Each task runs on its own branch created from the starting revision.
• If a task fails, Recipro stops and leaves the branch for inspection. Use --clean to reset.
• The ambient agent auto-disables after 3 consecutive API failures.