By zainw
Autonomous research-driven coding for Claude Code. Research options, present choices, implement with full verification. Inspired by Andrej Karpathy's autoresearch concept and pi-autoresearch by davebcn87.
Synthesize research findings from multiple researcher agents into a ranked comparison. Produces a weighted scoring table, pros/cons, and recommendation with top 3 options plus a "build custom" assessment.
Execute the chosen implementation approach. Makes all code changes in an isolated git worktree, commits frequently, handles complex multi-file refactors. Used for both initial implementation and auto-fix retries.
Deep-dive research on a single candidate solution. Evaluates library/approach quality, maintenance health, API design, bundle size, TypeScript support, and migration complexity. Returns structured findings.
Run multi-layer verification on implemented changes: tests, typecheck, lint, bundle analysis, benchmarks, and static analysis. Returns structured pass/fail/warn report.
Uses power tools
Uses Bash, Write, or Edit tools
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Autonomous research-driven coding for Claude Code.
# Add a new feature
/research add stripe subscription billing with webhook handling
# Fix a bug
/research fix the race condition in the WebSocket reconnect logic
# Refactor existing code
/research refactor the auth middleware to use JWT refresh tokens
autoresearch runs a six-step pipeline before writing a single line of production code:
| Step | Agent | What Happens |
|---|---|---|
| 1. Brief | Orchestrator (Sonnet) | Parses the task, writes .autoresearch/session.md with goals and constraints |
| 2. Research | Researcher × 3–5 (Sonnet) | Spawns parallel subagents, each deep-diving one candidate approach via web search and codebase analysis |
| 3. Evaluate | Evaluator (Sonnet) | Synthesizes all research findings, ranks approaches, outputs a structured recommendation |
| 4. Implement | Implementer (Opus) | Receives the top-ranked approach and implements it with full context, high effort |
| 5. Verify | Verifier (Sonnet) | Detects the project's toolchain and runs type-checks, tests, linting, and build |
| 6. Auto-fix | Implementer (Opus) | If verification fails, receives the error report and auto-fixes up to maxRetries times |
All state is written to .autoresearch/ in append-only logs. If the session is interrupted, it resumes automatically on the next Claude Code startup.
/plugin marketplace add ZainW/autoresearch
Start a research task:
/research <task description>
Clear session state (start fresh):
/research clear
Create .autoresearch/config.json in your project root to override defaults:
{
"maxRetries": 3,
"maxImplementerTurns": 50,
"maxResearchers": 5
}
| Option | Default | Description |
|---|---|---|
maxRetries | 3 | Max auto-fix attempts if verification fails |
maxImplementerTurns | 50 | Max turns for the implementer subagent per attempt |
maxResearchers | 5 | Number of parallel researcher subagents (3–5 recommended) |
| Step | Model | Reason |
|---|---|---|
| Brief | Claude Sonnet | Fast, structured parsing |
| Research | Claude Sonnet | Parallel — cost-efficient at scale |
| Evaluate | Claude Sonnet | Synthesis and ranking, no code generation |
| Implement | Claude Opus | Highest-quality code generation |
| Verify | Claude Sonnet | Toolchain detection and test execution |
| Auto-fix | Claude Opus | Bug fixes require the same quality as implementation |
This plugin would not exist without the work of two people:
Andrej Karpathy — for the autoresearch concept: the idea of autonomously researching multiple approaches before committing to an implementation.
davebcn87 — for pi-autoresearch, which established the implementation pattern this plugin is built on: persistent session state, append-only logging, and session resumability across interruptions.
This plugin adapts that pattern for Claude Code's native subagent architecture — replacing custom process orchestration with Claude Code's built-in agent dispatch, hooks system, and model-routing capabilities.
MIT. See LICENSE.
npx claudepluginhub zainw/autoresearchAutonomous research-driven coding for Claude Code. Research options, present choices, implement with full verification. Inspired by Andrej Karpathy's autoresearch concept and pi-autoresearch by davebcn87.
Spec-driven coding for Claude Code. Paste a spec, get reviewed code. Reviews specs for gaps, asks clarifying questions, routes to implementation based on prescriptiveness, and delivers verified code in an isolated branch.
PROJECT.md-first autonomous development with hybrid auto-fix documentation. 8-agent pipeline, auto-orchestration, docs auto-update on commit (true vibe coding). Knowledge base system with 90% faster repeat research. Strict mode enforces SDLC best practices automatically. Works for ANY Python/JavaScript/TypeScript/Go project.
Autonomous improvement engine for Claude Code. Runs an unbounded modify-verify-keep/discard loop against any mechanical metric. 10 subcommands: plan, debug, fix, security, ship, scenario, predict, learn, and reason.
No description provided.
Complete collection of battle-tested Claude Code configs from an Anthropic hackathon winner - agents, skills, hooks, and rules evolved over 10+ months of intensive daily use
Autonomous, personalized research loops for Claude Code. Set a topic, walk away, come back to a quality-gated report adapted to your projects.
Feature development with code-architect/explorer/reviewer agents, CLAUDE.md audit and session learnings, and Agent Skills creation with eval benchmarking from Anthropic.