Bootstrap Forge in the current project. Detects project type, configures validation commands, installs pre-commit hook, and vendors ralph-loop. Use this when setting up a new project for Forge spec runs and bead execution.
Create a subject-named specification from any evidence source using a reducer-based Forge workflow. Use this when the user wants a planning-ready spec, a clean-room reverse spec, or an evidence-first feature spec with sub-agent fanout, provenance tracking, adaptive clarification, speculative variants, and a canonical readiness contract.
Stamp a self-replicating four-bead autoresearch loop (doer/judge/arbiter/strategist) for autonomous iterative improvement of any artifact. Use after interactive intake when you have a program and want to run an autonomous improvement loop with blind scoring. Triggers on: autoresearch, research loop, autonomous loop, overnight loop, iterative improvement.
Decompose an implementation plan into br beads with dependency wiring, epic grouping, and provenance labels. Use this after spec-plan-handoff when the user accepts the beads generation prompt.
Stress-test beads for coverage, granularity, dependency correctness, and actionability using adversarial agent teams. Use this after spec-beads-generate when the beads workspace is populated.
Score a subject spec against the ontology and canonical readiness contract. Use this when you need claim-level coverage scoring, corroboration checks, critical-decision coverage, risk-weighted assumptions, contradiction penalties, and blocker-aware 80/80 gates.
Normalize all starting evidence into a subject spec run. Use this when beginning a Forge spec from code, docs, transcripts, screenshots, URLs, or a sparse user request. Creates the subject slug, frontmatter, evidence ledgers, request archetype, evidence-density classification, and canonical readiness skeleton.
Run the evidence-first Forge loop for a subject spec. Use this when you need to process evidence one unit at a time, produce unit summaries, rewrite the rolling summary, branch out to sub-agents for bounded exploration, choose adaptive clarification profiles, and emit speculative variants when blockers remain.