Autoresearch Python Packages

evo-hq-cli

turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.

evo-hq-agent

turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.

weco

Production-Grade Autoresearch. Ideal for GPU kernels, ML model development, feature engineering, prompt engineering, and other optimizable code.

autocontext

a recursive self-improving harness designed to help your agents (and future iterations of those agents) succeed on any task

etzchaim

A diagnosable brain for your LLM. Cognitive architecture in the SOAR/ACT-R/CLARION/LIDA lineage, for the LLM era. Apache 2.0.

arbor-agent

A generalist autonomous research agent — runs experiments, researches, and iteratively optimizes, autonomously.

schliff

Deterministic quality scorer for AI agent instruction files — 8-dimension scoring with security, multi-format (SKILL.md, CLAUDE.md, .cursorrules, AGENTS.md), anti-gaming detection, zero dependencies

research-git

Capture a code idea as a clean semantic unit, regenerate it onto today's codebase, aka, Agentic Git.

autocrucible

Autonomous experiment platform — let LLM agents optimize anything through iterative edit-evaluate loops

principia-ai

Principia extracts reusable principles, composes those principles into traceable research ideas, and helps researchers inspect why an idea may be worth testing.

aideml

AIDE: AI-Driven Exploration in the Space of Code. The machine Learning engineering agent that automates AI R&D.

autoctx

a recursive self-improving harness designed to help your agents (and future iterations of those agents) succeed on any task

tracecore

Deterministic runtime for agent evaluation

autoresearch-stack

Autonomous LLM training research stack - build and ship autonomous research systems

autoresearch-prompt-manager

Autonomous prompt management with versioning, A/B experiments, metrics, and LLM-driven optimization. Built on agno.

scholaraio

Scholar All-In-One — A research infrastructure for AI agents

marketing-agent-example

Example marketing content agent demonstrating the full prompt-manager stack

autoresearcher-shonku

Autonomous prompt management with versioning, A/B experiments, metrics, and LLM-driven optimization. Built on agno.

autoevolve

Companion tools for Karpathy's autoresearch - smarter evaluation, guided steering, and multi-agent competitions for GPT pretraining

autojudge

Smarter experiment evaluation for autoresearch — replaces eyeballing val_bpb with statistical verdicts

autosteer

Companion tools for Karpathy's autoresearch - smarter evaluation, guided steering, and multi-agent competitions for GPT pretraining

thehutch

Observability, steering, and provenance dashboard for autonomous-research agents.

ouro-loop

Give AI coding agents (Claude Code, Cursor, Aider, Codex) a structured autonomous loop with guardrails — boundaries, 5 verification gates, 3-layer self-reflection, and autonomous remediation. pip install ouro-loop. Zero dependencies.

shonku

Build, publish, and run AI agents as PyPI packages — wraps agno