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Awesome-Prompt-Engineering

This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
https://github.com/promptslab/Awesome-Prompt-Engineering

Last synced: 7 days ago
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AI Content Detectors

Free and Research Detectors

Leading Commercial Detectors

Apis

APIs

Anthropic (Claude)

Google (Gemini)

Meta (Llama)

OpenAI

Other Notable Providers

🔬 Autonomous Research & Self-Improving Agents

Domain-Specific Adaptations

  • mattprusak/autoresearch-genealogy - history research.
  • ArchishmanSengupta/autovoiceevals - or-revert prompt edits to harden voice AI agents across Vapi, Smallest AI, and ElevenLabs.
  • chrisworsey55/atlas-gic - or-revert loop to trading agents, optimizing prompts and portfolio orchestration against rolling Sharpe ratio instead of model loss.
  • RightNow-AI/autokernel
  • Rkcr7/autoresearch-sudoku - built solvers on hard benchmark sets.
  • jeongph/autospec - language business rules and autonomously builds a Spring Boot service with tests via the keep-or-revert loop. Evaluates with Gradle build + JUnit XML. 119-line skeleton to 950 lines in 5 cycles.
  • Agent-Analytics/autoresearch-growth - page positioning and A/B test candidates, using analytics snapshots and measured experiment results to seed subsequent rounds.
  • ElliotXie/autozyme - agent framework that applies the autoresearch keep-or-revert loop to CPU-side scientific software: profile a target function, generate one optimization candidate, benchmark for speed while preserving the original outputs, keep or revert, repeat.
  • vlasenkoalexey/tpu_performance_autoresearch_wiki - or-revert loop to TPU model performance (MFU / tokens-per-sec) on v6e hardware: profiles each run through an XProf MCP server, makes one model-code change per experiment, and keeps or reverts against measured MFU. Pairs the loop with a Karpathy-style LLM wiki for domain knowledge and per-experiment optimization traces; includes Llama3-8B and Qwen3-8B case studies across JAX and torchax lanes.

Evaluation & Benchmarks

General-Purpose Descendants

GitHub Organizations

Platform Ports & Hardware Forks

Related Resources

Research-Agent Systems

  • aiming-lab/AutoResearchClaw - 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.
  • OpenRaiser/NanoResearch - 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.
  • wanshuiyin/Auto-claude-code-research-in-sleep - first research workflows for Claude Code and other agents, centered on autonomous literature review, experiments, paper iteration, and cross-model critique.
  • Sibyl-Research-Team/AutoResearch-SibylSystem - agent research iteration, GPU experiment execution, and a self-evolving outer loop.
  • eimenhmdt/autoresearcher - source package for automating scientific workflows, currently centered on literature-review generation with an ambition toward broader autonomous research.
  • hyperspaceai/agi - to-peer research network where autonomous agents run experiments, gossip findings, maintain CRDT leaderboards, and archive results to GitHub across multiple research domains.
  • SakanaAI/AI-Scientist
  • SakanaAI/AI-Scientist-v2 - level automated scientific discovery via agentic tree search. Removes template dependency from v1, generalizes across research domains.
  • HKUDS/AI-Researcher - to-end research automation: hypothesis → experiments → manuscript → peer review. Production version at novix.science.
  • openags/Auto-Research
  • SamuelSchmidgall/AgentLaboratory - to-end autonomous research workflow: idea → literature review → experiments → report. Supports both autonomous and co-pilot modes.
  • AgentRxiv
  • JinheonBaek/ResearchAgent - agent review and feedback loops.
  • du-nlp-lab/MLR-Copilot
  • MASWorks/ML-Agent
  • PouriaRouzrokh/LatteReview - code Python package for automated systematic literature reviews via AI-powered agents.
  • LitLLM/LitLLM - powered literature review assistant using RAG for accurate, well-structured related-work sections in academic writing.
  • Agent Laboratory - phase research pipeline: Literature Review → Experimentation → Report Writing, with specialized agents for each phase.
  • Human-Agent-Society/CORAL - agent evolution for open-ended discovery (arXiv:2604.01658). Long-running agents with shared persistent memory, asynchronous execution, and heartbeat-based interventions; SOTA on 10 math/algorithmic/systems tasks.
  • skyllwt/OmegaWiki - centric full-lifecycle research platform built on Claude Code, realizing Karpathy's LLM-Wiki vision. 20+ skills cover the full loop: ingest → ideate → novelty check → experiment design / run / eval → paper writing. Research state lives in a structured knowledge wiki with an interactive graph.
  • AweAI-Team/AiScientist - horizon ML research lab with hierarchical orchestration and File-as-Bus coordination — workspace files act as the durable system of record. Drives autonomous paper-reproduction (PaperBench) and competition-style MLE-Bench iteration loops under fixed compute/time budgets. (arXiv 2604.13018)
  • kaust-ark/ARK
  • skyllwt/AutoSci - centric full-lifecycle research platform built on Claude Code, realizing Karpathy's LLM-Wiki vision. 20+ skills cover the full loop: ingest → ideate → novelty check → experiment design / run / eval → paper writing. Research state lives in a structured knowledge wiki with an interactive graph.
  • happyhappy-jun/writing-driven-autoresearch - style harness that keeps a submittable paper from the first minute and drives every experiment from the claims in that draft, looping modify → measure → verify → revise. 1st place at the Ralphthon@ICML 2026 autonomous-research hackathon.
  • AutoResearch-Factory/Agon - to-end research orchestrator built on one cornerstone principle, Prompt Economy (reusable loops, not one-off prompts), plus five supporting rules; runs scientist/coder/auditor loops across 10+ disciplines, same reusable-loop lineage as autoresearch but scaled to full research programs.

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Major Benchmarks (2024–2026)

Prompt and Instruction Datasets

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Agentic Prompting and Multi-Agent Systems