claude

dark-factory

Dark Factory: Autonomous AI development pipeline with governance tiers, holdout validation, satisfaction judging, and Ralph Wiggum loop.

0 on GitHubby Evervav1.3.3MITupdated 4 months agoautomation
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Plugin dark-factory from marketplace everva in everva/claude-plugins. Commands read from the repo's manifest — 1 month 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 (7)

  • dashboard

    Show Dark Factory observability dashboard — session metrics, quality scores, Ralph loop status, backlog summary.

  • factory

    Dark Factory — start/stop/status of the Ralph Wiggum autonomous loop, sync backlog, run single task, or validate sessions.

  • init

    Initialize Dark Factory in a new project — creates .dark-factory/ directory, config.yaml, backlog, governance docs, and example holdout.

  • readiness

    Evaluate project readiness for Dark Factory autonomous development. Scores 8 axes and produces a scorecard.

  • satisfaction

    Run two-pass adversarial LLM quality evaluation on a completed feature implementation.

  • task

    Start a new development task through the Dark Factory pipeline. Analyzes task, classifies size, and routes to implementation.

  • validate

    Validate a completed Dark Factory session — show governance decision, metrics, and recommended actions.

Subagents (6)

  • holdout-validator

    Validates implementation against hidden behavioral scenarios that the implementation agent never saw.

  • pipeline-doctor

    Self-healing agent that diagnoses and fixes pipeline failures. Analyzes error logs, identifies root causes, generates targeted fixes.

  • readiness-auditor

    Evaluate project readiness for autonomous development. Scores 8 axes and produces a JSON scorecard.

  • regression-runner

    Run test suites across the project to catch regressions. Use after significant changes or before merging major features.

  • satisfaction-judge

    Two-pass adversarial LLM evaluation of implementation quality across 5 dimensions.

  • task-analyzer

    Analyze incoming tasks: classify size (XS/S/M/L/XL), identify affected areas, detect dependencies, recommend pipeline depth.

Hooks (1)

  • PreToolUse

    ${CLAUDE_PLUGIN_ROOT}/scripts/holdout-guard.sh

View source on GitHub

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