claude

build-loop-auto-research

Build-loop extension with Karpathy's autoresearch pattern: constrained scope + mechanical metric + git commit/revert + autonomous iteration for app development optimization.

0 on GitHubby Tyrone Rossv0.2.0MITupdated 3 days ago

Not in a marketplace yet, so it loads for one session with --plugin-dir.

Plugin build-loop-auto-research in tyroneross/RossLabs-AI-Toolkit. Commands read from the repo's manifest — 2 days ago.

This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.

What it installs

Skills (9)

  • analyze-history

    Use when the user wants to analyze prior Codex archived sessions to infer request, authorization, verification, and handoff patterns and use those patterns to improve future build workflows.

  • autoresearch-loop

    Autonomous metric-driven optimization loop. Constrained scope + mechanical metric + git commit/revert + fast iteration. Use for build optimization, test coverage, prompt tuning, doc quality, or runtime performance.

  • build-loop-auto-research

    Use for significant multi-step research-and-planning work that benefits from a phase-based loop, orchestration, parallel subagents, validation, iteration, and context continuity.

  • context-restore

    Use when resuming work in a project that may already have a build-loop-auto-research context snapshot or registry fallback trailhead.

  • context-snapshot

    Use when work is about to span sessions, risk compaction, or switch contexts and you want a bookmark-style local snapshot of the current project state.

  • memory-lookup

    Use before repeating an investigation, debugging loop, or multi-iteration fix so Codex can check modular lessons learned and decide whether a known fix or likely match already exists.

  • optimize-brief

    Use when the user has a rough request, draft plan, or prompt that needs to be tightened into a clearer, simpler, more verifiable build brief.

  • pattern-aware-planning

    Use when a user wants a research-backed build packet, a concise build investigation, a history-pattern analysis, or a brief/prompt optimization pass.

  • research-build

    Use when the user wants a research packet plus a decision-complete implementation plan for a product, feature, algorithm, prompt, bugfix, or refactor, but does not need the full explicit phase-by-phase build loop narration.

Slash commands (11)

  • /build-loop-auto-research:analyze-history

    Analyze Codex archived sessions and infer request / authorization / verification patterns

  • /build-loop-auto-research:autoresearch-plan

    Define an autoresearch experiment without running it. Interactive wizard for scope, metric, guard, and budget.

  • /build-loop-auto-research:autoresearch-run

    Execute the autoresearch loop using an existing experiment.json configuration.

  • /build-loop-auto-research:autoresearch-status

    Show the current autoresearch experiment state, results, and progress.

  • /build-loop-auto-research:autoresearch

    Run autonomous metric-driven optimization. Constrained scope + mechanical metric + git commit/revert + fast iteration.

  • /build-loop-auto-research:build-loop-auto-research

    Orchestrated research-backed build loop: assess → define → plan → execute → validate → iterate → fact-check → report

  • /build-loop-auto-research:context-restore

    Restore the latest bookmark-style local context snapshot for the current project

  • /build-loop-auto-research:context-snapshot

    Capture a bookmark-style local context snapshot for the current project

  • /build-loop-auto-research:memory-lookup

    Search modular lesson memory and return a debugger-style verdict before repeating an investigation

  • /build-loop-auto-research:optimize-brief

    Tighten a rough request, plan, or prompt into a clearer build brief with verification guidance

  • /build-loop-auto-research:research-build

    Create a research packet and decision-complete build plan for a product, feature, algorithm, prompt, bugfix, or refactor

Subagents (9)

  • autoresearch-runner

    Executes the autoresearch optimization loop. Generates hypotheses, makes atomic changes within scope, measures metrics, keeps improvements or reverts regressions. Runs autonomously until convergence or budget exhaustion.

  • build-loop-auto-research-orchestrator

    Coordinates the build-loop-auto-research 8-phase loop for research-backed build planning.

  • evidence-checker

    Validates evidence quality, confidence level, and whether more iteration is required.

  • integration-checker

    Reviews integration points, handoffs, contracts, and deployment/runtime constraints before execution.

  • issue-investigator

    Investigates issue-like tasks with memory-first lookup, root-cause reasoning, verification, and iteration discipline.

  • memory-curator

    Captures modular lessons learned when work takes multiple iterations or an integration assumption fails.

  • overfitting-reviewer

    Reviews autoresearch experiment results for overfitting, Goodhart violations, and test-gaming shortcuts. Read-only adversarial review. Checks that improvements are genuine and generalizable, not test-harness artifacts.

  • repo-context-scanner

    Scans the repo, identifies likely entrypoints, tests, and integration surfaces, and returns a compact repo-grounding brief.

  • research-orchestrator

    Produces a research-backed build packet for a product, feature, algorithm, prompt, bugfix, or refactor. <example> Context: user wants a feature investigation with a concrete build path user: "Figure out the best way to add prompt versioning to this repo" assistant: "I'll use the research-orchestrato

Hooks (2)

  • SessionStart
  • PostToolUse
View source on GitHub rosslabs.ai

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