Autoresearch
Autonomous research loop inspired by karpathy/autoresearch — give it a plain-language goal; it infers a recommended contract, then grills each decision with you (goal…
Plugin bundle · by Frad LEE
About
Autoresearch is a plugin bundle for AI coding tools published by Frad LEE. Marketplaces we read that list it: 1 (Community GitHub marketplaces). The last change we recorded was on 2026-10-20. As of our marketplace pass on 2026-10-24.
Autonomous research loop inspired by karpathy/autoresearch — give it a plain-language goal; it infers a recommended contract, then grills each decision with you (goal measurability, artifact, evaluator, bounds) before iterating: cheap sequential rounds that escalate to a parallel GAN tournament when they plateau
What it asks for
- Installs as a plugin bundle
- Hooks: 1
What it declares, asks for and runs, in full
Only install plugins from developers you trust. We list what marketplaces publish and do not test plugins.
Works with
- Claude Code
From the marketplaces that list it and the MCP transport it declares, as each client documents them. We do not test plugins.
Connect
Commands and configs built only from what its marketplaces declare. We do not run them for you and do not test plugins.
As a Claude Code plugin
Built from what Community GitHub marketplaces declares.
/plugin marketplace add fradser/dotclaude
/plugin install autoresearch@frad-dotclaudeWhere it is published
| Marketplace | Status | Version | Figures | Verified | First seen |
|---|---|---|---|---|---|
| Community marketplace fradser/dotclaude (Open the source on GitHub) | Listed | 0.9.2 | Forks (GitHub): 51 Stars (GitHub): 596 |
Not marked |
Each figure is the marketplace's own and is never added up across marketplaces. A marketplace that publishes no figure shows none: no number is not zero.
Listed in one community marketplace
| Marketplace | Repository | Stars (GitHub) |
|---|---|---|
| frad-dotclaude | fradser/dotclaude | 596 |
How its figures have moved
- 2026-10-2051
- 2026-10-2451
- 2026-10-20596
- 2026-10-24596
Each dot is a day we read a different number; flat stretches are days the number did not move. Figures of different marketplaces are never added up.
What the bundle contains
As published on Community GitHub marketplaces.
Commands: 3
cancelhelpstart
Hooks: 1
Stop
What changed
- Became a product we track
- Community GitHub marketplaces: appeared
Similar plugins
Products whose own names, descriptions, tools and skills are closest in meaning to this one, on every marketplace we read. Closeness is ranked within this list only.
-
Apply Karpathy's autoresearch loop (goal + mechanical fitness + mutable surface + keep-or-revert iteration) to ANY measurable workflow - code, content, sales, research, design…
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
-
Autonomous prompt optimization using Karpathy's autoresearch pattern. Editable file + fixed eval metric + autonomous improvement loop.
-
lazy-developer
Orchestrates autoresearch across a prioritized sequence of optimization goals — with configurable phase order and optional ralph-driven execution
-
Set up autonomous goal-driven optimization — creates a GOAL.md fitness function and runs an improvement loop
-
Automated AI research toolkit: hypothesis generation, experiments, and paper writing
-
Reviewable ML research: literature, planning, methodology review, bounded runs, sweeps, implementation verification, ablations, retrospectives, Kaggle, and setup
-
Autonomous experiment loop — modify, test, keep/discard, repeat forever
-
Drop-in agentic loop skills (autoresearch, literature & writing, data, optimization, red-team, power analysis). Skills install namespaced as agent-loops:<name>.
-
Autonomous SKILL.md improvement via Karpathy autoresearch-inspired iterative eval hill-climbing with force iteration, NEUTRAL mutation judgment, mutation exclusions, L1/L2/L3 eval…
Similar plugins by marketplace
The same question asked of one marketplace at a time: is there an analog of this plugin there?
Has a listing on Claude Code: claude-plugins-community (5)
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
-
Autonomous prompt optimization using Karpathy's autoresearch pattern. Editable file + fixed eval metric + autonomous improvement loop.
-
Autonomous skill improvement through parallel research agents. Inspired by Karpathy's autoresearch methodology, it spawns 5 parallel agents (domain expert, quality auditor…
-
Autonomous experiment loop for Claude Code. Run an endless optimize-measure-keep/discard cycle on any optimization target: LLM training loss, test speed, bundle size, build time…
-
Multi-agent deep research pipelines for Claude Code. Runs internet research, repository analysis, schema-driven structured research, and media research (via NotebookLM) using…
Has a listing on Claude Code: claude-plugins-official (5)
-
Interactive self-referential AI loops for iterative development, implementing the Ralph Wiggum technique. Claude works on the same task repeatedly, seeing its previous work, until…
-
Build, train, evaluate, and use open source AI models, datasets, and spaces.
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Comprehensive development workflow for building AI agents with the Atomic Agents framework. Includes specialized agents for schema design, architecture planning, code review, and…
-
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
Has a listing on Claude: knowledge-work-plugins (5)
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
AI-first project auditor and re-engineer based on the 9 design principles and 7 design patterns from the TechWolf AI-First Bootcamp
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
A suite of agent skills for the full GrowthBook feature flag and experimentation lifecycle.
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
Has a listing on Codex: openai-curated (openai/plugins) (5)
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
An agentic skills framework & software development methodology that works: planning, TDD, debugging, and collaboration workflows.
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
CrowdStrike Falcon Foundry development skills for building cybersecurity applications on the Falcon platform. Includes UI development, collections, functions, workflows, API…
Has a listing on Community GitHub marketplaces (5)
-
Apply Karpathy's autoresearch loop (goal + mechanical fitness + mutable surface + keep-or-revert iteration) to ANY measurable workflow - code, content, sales, research, design…
-
Autonomous experiment loops on any codebase — one file, one metric, one loop. An agent edits a constrained file, runs an eval, keeps improvements, reverts failures, and repeats…
-
lazy-developer
Orchestrates autoresearch across a prioritized sequence of optimization goals — with configurable phase order and optional ralph-driven execution
-
Set up autonomous goal-driven optimization — creates a GOAL.md fitness function and runs an improvement loop
-
Automated AI research toolkit: hypothesis generation, experiments, and paper writing
Has a listing on Copilot CLI: github/awesome-copilot (5)
-
Goal-driven task orchestration with independent verification. Interviews the user to define a clear goal, then loops between a Builder subagent (does the work) and an Inspector…
-
Premium planning, thrifty implementation
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Task Researcher and Task Planner for intermediate to expert users and large codebases - Brought to you by microsoft/edge-ai
-
Record your screen doing a manual process, drop the video on your Desktop, and let Copilot CLI analyze it frame-by-frame to build working automation scripts. Supports narrated…
Has a listing on Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
Bring Azure DevOps work-item, repository, and pull-request workflows into GitHub Copilot.
-
model-apps
Build and deploy Power Apps generative pages for model-driven apps with specialist agents for planning, entity creation, and parallel code generation. Requires PAC CLI >= 2.7.0…
-
Advanced Security plugin for GitHub Copilot.
-
Complete bundle: all Microsoft Skills for Fabric for developers and consumers.
Has a listing on Cursor: cursor/plugins (5)
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
Consult a stronger model before major decisions, when stuck, and before declaring done.
-
if you want to go fast, go deep first. pstack helps you write less, but higher quality code. rigorous agent workflows you can parallelize with confidence.
-
Patterns for designing CLIs that coding agents can run reliably: flags, help with examples, pipelines, errors, idempotency, dry-run.
-
Fan large tasks out across parallel cloud agents with planners, workers, verifiers, and structured handoffs.
Has a listing on Docker MCP Catalog (5)
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Sequential Thinking (Reference)
Dynamic and reflective problem-solving through thought sequences.
-
Real-time web search, reasoning, and research through Perplexity's API
-
Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.
-
Tools for interacting with Hugging Face models, datasets, research papers, and more.
Has a listing on Official MCP Registry (5)
-
Automated AI research toolkit: hypothesis generation, experiments, and paper writing
-
openpaper-mcp io.github.federicodeponte/openpaper-mcp
Autonomous research engine: auto research from a prompt to a fully-cited academic paper via MCP
-
forkmind io.github.Medhovarsh/forkmind
Branchable LLM history DAG + encrypted context capsules agents can save, restore, and crypto-shred.
-
agentic-research io.github.TheAiSingularity/agentic-research
Local research agent that verifies its own answers. Runs on Gemma 3 4B + Ollama, $0/query.
-
Create, launch, and analyze user research studies, AI interviews, and AI tests from your AI agent.
Has a listing on PyPI (MCP servers) (5)
-
Search Lacuna's ML research graph for papers, directions, authors, venues, and hypotheses.
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
hypermnesia-mcp io.github.cdeust/hypermnesia-mcp
Persistent memory for AI agents — 36 cited neuroscience mechanisms, local-first, hybrid retrieval.
-
Let one coding-agent CLI consult another: Codex, Claude Code, OpenCode, Copilot or Antigravity.
-
parallel com.mcparmory/parallel
Search the web, extract content, and run distributed tasks with AI-powered automation
Has a listing on npm registry (MCP servers) (5)
-
review-assist-mcp io.github.uditk2/review-assist-mcp
Turns an AI coding agent session into a reviewable Intent Document, validated against the diff.
-
Local MCP server for AI coding safety: risk checks, sessions, checkpoints, and fix prompts.
-
google-surf-mcp io.github.HarimxChoi/google-surf-mcp
Web, academic and code search with graph RAG, data lineage, ontology and cross-project schema links.
-
gitmem io.github.gitmem-dev/gitmem
Persistent institutional memory for AI coding agents. Memory that compounds.
-
Hands bounded coding work to cheaper worker agents: verified answers, exact diffs, cost receipts.
Found by meaning, not by shared code or a shared repository: similar plugins stay separate products, and this is not a review or a recommendation.
Want this mark on your plugin in our catalog?
Prove you maintain it with a file in its repository, a file on your domain or a DNS record, and you can show this mark on the card, with live banners for your site and README. How verification works
You also get alerts when a marketplace lists it, drops it, changes its verified mark or what it asks for, and its remote endpoint goes on monitoring as a web service.
Data comes from public marketplace files in GitHub repositories of their authors. Figures come from our own regular passes over the marketplaces, last read on . We publish no contact details for plugin publishers.