RSI Loop v0.1.0 — Universal Self-Improvement for AI Agents

Every AI agent makes mistakes. RSI Loop makes them learn.

A framework-agnostic recursive self-improvement loop that works with any AI agent — Claude Code, Codex, Cursor, Antigravity, OpenClaw, EvoClaw, or your own.

Features

• Observer — Auto-classify issues, recurrence detection, JSONL persistence
• Analyzer — Pattern detection, error similarity, cross-source correlation, health scoring
• Fixer — Auto-fix safe categories, proposal generation for unsafe ones
• Loop — Background thread with periodic analyze → fix cycles

Integrations

• Claude Code / OpenClaw adapter
• Generic file-based adapter (works anywhere)
• Webhook adapter (HTTP POST)

Quick Start

uv add rsi-loop

from rsi_loop import RSILoop

loop = RSILoop()
loop.observer.record_simple('code_generation', success=True, model='sonnet-4.6')
print(loop.health_score())  # 0.0 - 1.0

Stats

• 72 tests, 91% coverage
• Zero dependencies (stdlib only)
• Python 3.10+

Full docs: architecture | sources | auto-fix

Built by ClawInfra — infrastructure for autonomous agents.