mit einem Klick
dark-factory
dark-factory enthält 5 gesammelte Skills von jleechanorg, mit Repository-Berufsabdeckung und Skill-Detailseiten auf SkillsMP.
Skills in diesem Repository
End-to-end auto-factory driver — picks up beads + GH issues tagged factory, dispatches coders to drive worldai PRs to /green + /advice + /er, runs verifier ticks, repeats until done. Designed to work even when GH API is rate-limited (falls back to beads-only).
Run the Dark Factory DOT pipeline runner against a goal. Slash command: /factory. Implements StrongDM's Attractor pattern as an external Python runner — .dot files are the versioned artifact, sealed holdouts live in a separate repo, every step is recorded to CXDB, and the Healer clusters failures into diagnoses. Use when you want the goal_harness idea executed as a reproducible external pipeline instead of in-Claude subagent dispatch.
Dark Factory two-phase spec workflow (/factory-spec, /fs): create a main spec (spec.md) AND an attractor spec (attractor_spec.md) via the spec_gen pipeline, review an existing spec of either kind, or display the pipeline node graphs — spec-review pipelines, factory gates, node types, edge conditions, handler mappings. Create mode runs dark-factory --pipeline slim/spec_gen.dot; both the main and attractor specs must be codex-cold-reviewed and pass before exit. Review and show modes are in-session only.
Build a developer reproduction bundle for agent-review failures, missed-plan retrospectives, Claude/Codex transcript comparisons, or cases where Anthropic/OpenAI engineers need raw conversation JSONL, subagent state, repo evidence, hashes, and a concise replay guide.
Run matched A/B reviewer calibration for /f: compare factory reviewer, raw codex exec, and delegated subagent reviews on the same frozen PR/work-item envelope.