Orchestrate the full AIDLC Autonomous Pipeline from a one-sentence requirement to a PR-ready delivery with TDD methodology. DDD drives judgment, SDD produces specs, TDD verifies delivery. Stages: Evaluate, Think, Plan, Build, Review, Test, Deliver, Reflect. Checkpoints on BLOCK or context limits. TRIGGER: "run pipeline", "autonomous pipeline", "pipeline for", "full pipeline". NOT FOR: single stages (use evaluate, deep-research, code-review, qa, deliver directly).
DDD-native autonomous dev loop — judge→execute→reflect on a SINGLE DDD via a bundled, decoupled engine (engine/artifact_cli.py, file-based .artifacts/ state, NO data.db, NO SwarmAI backend). Retains the moat: Gate-2 adversarial-before-commit + the 养成 ladder. DDD-native decouple of SwarmAI's s_autonomous-pipeline engine. TRIGGER: "ddd pipeline", "run the ddd loop", "build in this ddd". NOT FOR: SwarmAI's own multi-project pipeline (that's the native s_autonomous-pipeline).
Package a grown DDD into a distributable capability package — the last step of the DDD lifecycle (cultivate → version → DISTRIBUTE). Human-in-the-loop: reads the DDD's OWN declared reach (aim.json distribution block = the ceiling), confirms which declared target(s) to emit NOW, renders BOTH standard shapes on demand — an internal AIM capabilities package (Config+AIMBuild+agent-spec) and/or an Open-Plugins plugin (.plugin/plugin.json) — runs a fail-closed content-safety scan over the emitted tree, and returns the built package path. Never widens reach by inference; emit ≠ publish. TRIGGER: "distribute this ddd", "package ddd", "ship ddd to kiro/quick/claude code", "publish ddd", "make a plugin from this ddd". NOT FOR: creating/binding a DDD (s_ddd-manager); running the pipeline (s_ddd-pipeline); publishing content/media (s_ddd-pollinate).
Create, list, edit, rename, and delete DDD projects (Domain-Driven Design) — provisions the canonical six-section DDD structure. Each project gets 4 knowledge documents (PRODUCT.md, TECH.md, IMPROVEMENT.md, PROJECT.md) and an .artifacts/ directory for pipeline outputs. TRIGGER: "add project", "new project", "create project", "rename project", "create DDD". NOT FOR: radar-todo use cases.
Estimate token count for files using the bundled script. TRIGGER: "estimate tokens", "count tokens", "token usage", "context window size". DO NOT USE: for manual token math — always run the script.
Full SwarmAI release cycle: preflight checks, version bump, binary build, desktop package, smoke test, and GitHub publish. Supersedes s_release (which only does version bump + tag) by adding build/package/smoke stages. TRIGGER: "release", "cut release", "ship it", "发版". NOT FOR: s_swarm-build, s_release, s_swarm-hive use cases.
Persist knowledge to the correct destination — routes to DDD docs (PRODUCT/TECH/IMPROVEMENT/PROJECT), MEMORY.md, Knowledge/Library/ (searchable store), or EVOLUTION.md based on content type. Unified routing for both manual saves and auto hooks. TRIGGER: "remember", "save", "persist", "沉淀", "record this", "save to DDD", "save lessons". NOT FOR: save-context, save-activity, self-evolution (governance rules) use cases.
Generate AI-Ready artifacts for any codebase — transforms repos into DDD-structured context (AGENTS.md + PRODUCT/TECH/IMPROVEMENT/PROJECT.md + code-intel.json) that makes AI agents truly understand the project. Works on any language, any framework. TRIGGER: "make AI-ready", "ai-ready repo", "generate DDD for repo", "analyze codebase". NOT FOR: code-review, deep-research use cases.