awesome-autoresearch
by alvinunreal
A curated list of autonomous improvement loops, research agents, and autoresearch-style systems inspired by Karpathy's autoresearch.
1,052stars
78forks
Added 3/24/2026
Installation
# Add to your Claude Code skills
git clone https://github.com/alvinunreal/awesome-autoresearchGetting Started
Guides for using ai agents skills like awesome-autoresearch.
Security ReportVerified
Last scanned: 5/1/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-05-01T06:40:03.239Z",
"semgrepRan": false,
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}🔬 Awesome Autoresearch
A curated, high-signal index of autonomous improvement loops, research agents, and descendants inspired by karpathy/autoresearch.
by Boring Dystopia Development
Contents
- 🛠️ General-purpose descendants
- 🔬 Research-agent systems
- 💻 Platform ports and hardware forks
- 🎯 Domain-specific adaptations
- 📊 Evaluation & benchmarks
- 📈 Notable use cases and writeups
- 📚 Related resources
- 📄 License
🛠️ General-purpose descendants
- uditgoenka/autoresearch
- Claude Code skill that generalizes autoresearch into a reusable loop for software, docs, security, shipping, debugging, and other measurable goals.
- leo-lilinxiao/codex-autoresearch - Codex-native autoresearch skill with resume support, lessons across runs, optional parallel experiments, and mode-specific workflows.
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- Gemini CLI skill that generalises autoresearch to any measurable goal. Gemini-native: uses Google Search grounding as a live verification source inside the loop, true headless overnight mode via --yolo --prompt, and 1M token context. Also works in Antigravity IDE via .agents/skills/.
- 
- Claude Code plugin/skill port of 
- Closed-loop control plane for repeated agent improvement, with evaluation, persistent knowledge, staged validation, and optional distillation into cheaper local runtimes.
- Generalizes autoresearch into a 
- Collaborative fork of upstream autoresearch that adds experiment claiming, shared best-config syncing, hypothesis exchange, and swarm-style coordination across many single-GPU agents.
- Generalizes autoresearch to any measurable metric — system prompts, API performance, landing pages, test suites, config tuning, SQL queries. "If you can measure it, you can optimize it."
- Cross-platform expansion that auto-detects hardware config and starts the loop. The "glue and generalization" half of autoresearch.
- Automated Design of Agentic Systems — ICLR 2025. Meta-agents that invent novel agent architectures by programming them in code.
- SICA: Self-Improving Coding Agent that edits its own codebase. ICLR 2025 Workshop paper demonstrating scaffold-level self-improvement on coding benchmarks.
- Alternative self-improving agent architecture with reflection and meta-learning cycles.
- Huxley-Gödel Machine for coding agents — applies self-improvement to SWE-bench performance via meta-level optimization.
- GEPA (Genetic-Pareto) — ICLR 2026 Oral. Reflective prompt evolution that outperforms RL (GRPO) on benchmarks. Optimizes any textual parameters against any metric using natural language reflection.
- GEPA-inspired autoresearch for self-play: mutate code strategies, evaluate head-to-head, rate with Elo/Bradley-Terry, branch from the Pareto front. Agent reads match traces to target mutations. Works as a Claude Code skill.
- Agent swarm intelligence for autoresearch — spawns parallel GPU research directions, distributes work across agents, aggregates results.
- Comprehensive skill library including autoresearch orchestration with two-loop architecture (inner optimization + outer synthesis).
- AIDE: Tree-search ML engineering agent that autonomously improves model performance via iterative code generation and evaluation.
- End-to-end research pipeline that turns a topic into literature review, experiments, analysis, peer review, and paper drafts; broader than autoresearch, but clearly in the same lineage.
- End-to-end autonomous research engine that plans experiments, generates code, runs jobs locally or on SLURM, analyzes real results, and writes papers grounded in those outputs.
- Markdown-first research workflows for Claude Code and other agents, centered on autonomous literature review, experiments, paper iteration, and cross-model critique.
- Fully autonomous AI scientist built on Claude Code, with explicit AutoResearch lineage, multi-agent research iteration, GPU experiment execution, and a self-evolving outer loop.
- Early open-source package for automating scientific workflows, currently centered on literature-review generation with an ambition toward broader au