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repo-to-ddd

スター29

フォーク3

更新日2026年7月22日 14:49

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.

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xg-gh-25

xg-gh-25/SwarmAI

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Repo to DDD

This skill loads full instructions on activation. Read INSTRUCTIONS.md before proceeding.

TRIGGER: "make AI-ready", "ai-ready repo", "generate DDD", "analyze codebase for AI"

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ddd-distribute

xg-gh-25/SwarmAI

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).

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pollinate

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Swarm's media value delivery engine. Transforms messages into optimized media packages (poster, video, narrative, shorts, README) via a 9-stage pipeline (EVALUATE->REFLECT). Message-first, format follows audience. Your message, their attention, the right format. TRIGGER: "pollinate", "make content about", "GTM for", "promote". NOT FOR: autonomous-pipeline, deep-research use cases.

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ddd-manager

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Provision and manage DDD projects that conform to the canonical six-section structure — the self-propagation seed. Full lifecycle: CREATE (with context-extraction from a codebase, NOT blank templates), BIND a repo (⑤ delivery contract), LIST / EDIT / RENAME. Pure filesystem, no SwarmAI backend — a DDD carries this so it can create MORE spec-compliant DDDs on Kiro / Claude Code. TRIGGER: "create ddd", "new ddd project", "add a domain", "bind repo to ddd", "provision ddd". NOT FOR: SwarmAI's own project CRUD (native s_project-manager); code (that's s_ddd-pipeline).

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ddd-pipeline

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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).

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ddd-pollinate

xg-gh-25/SwarmAI

Express THIS DDD's product value to audiences — message-first, format follows — via a bundled, decoupled copy of SwarmAI's real pollinate engine (11 format tracks + scripts + moat gates), sourcing value from the DDD's own ② PRODUCT.md, file-based, no SwarmAI backend. DDD-native decouple of s_pollinate. TRIGGER: "ddd pollinate", "express this ddd's value", "make content from this ddd". NOT FOR: SwarmAI's own s_pollinate (bound to Swarm brand + SwarmWS paths).

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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.

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name	repo-to-ddd
description	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.
tier	lazy
platform	all

name	repo-to-ddd
description	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.
tier	lazy
platform	all