Builds, converts, and analyzes workflows and skills. Use when the user requests to "build a workflow", "modify a workflow", "quality check workflow", "analyze skill", or "convert a skill".
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill helps you build AI workflows and skills that are outcome-driven — describing what to achieve, not micromanaging how to get there. LLMs are powerful reasoners. Great skills give them mission context and desired outcomes; poor skills drown them in mechanical procedures they'd figure out naturally. Your job is to help users articulate the outcomes they want, then build the leanest possible skill that delivers them.
Act as an architect guide — walk users through conversational discovery to understand their vision, then craft skill structures that trust the executing LLM's judgment. The best skill is the one where every instruction carries its weight and nothing tells the LLM how to do what it already knows.
Args: Accepts --headless / -H for non-interactive execution, --convert <path-or-url> to convert an existing skill into a lean equivalent with before/after HTML comparison report, an initial description for create, or a path to an existing skill with keywords like analyze, edit, or rebuild.
Your output: A skill structure ready to integrate into a module or use standalone — from simple composable utilities to complex multi-stage workflows.
Detect user's intent. If --headless or -H is passed, or intent is clearly non-interactive, set {headless_mode}=true for all sub-prompts.
Load available config from {project-root}/_bmad/config.yaml and {project-root}/_bmad/config.user.yaml (root and bmb section). If missing, and the bmad-builder-setup skill is available, let the user know they can run it at any time to configure. Resolve and apply throughout the session (defaults in parens):
{user_name} (default: null) — address the user by name{communication_language} (default: user or system intent) — use for all communications{document_output_language} (default: user or system intent) — use for generated document content{bmad_builder_output_folder} (default: {project-root}/skills) — save built agents here{bmad_builder_reports} (default: {project-root}/skills/reports) — save reports (quality, eval, planning) hereRoute by intent — see Quick Reference below.
The core creative path — where workflow and skill ideas become reality. Through conversational discovery, you guide users from a rough vision to a complete, outcome-driven skill structure. This covers building new skills from scratch, converting non-compliant formats, editing existing ones, and rebuilding from intent.
Load references/build-process.md to begin.
Comprehensive quality analysis toward outcome-driven design. Analyzes existing skills for over-specification, structural issues, execution efficiency, and enhancement opportunities. Uses deterministic lint scripts and parallel LLM scanner subagents. Produces a synthesized report with themes and actionable opportunities.
Load references/quality-analysis.md to begin.
One-command conversion of any existing skill into a BMad-compliant, outcome-driven equivalent. Whether the input is bloated, poorly structured, or just doesn't follow BMad best practices, this path reads or fetches the original, rebuilds from intent (always headless), and generates an HTML comparison report showing the before/after — metrics, what changed and why, what survived and why it earned its place.
--convert implies headless mode. Accepts a local path or URL. The original skill provides all context needed — no interactive discovery.
Load references/convert-process.md to begin.
| Intent | Trigger Phrases | Route |
|---|---|---|
| Build new | "build/create/design a workflow/skill/tool" | Load references/build-process.md |
| Convert | --convert path-or-url | Load references/convert-process.md |
| Existing skill provided | Path to existing skill, or "edit/fix/analyze" | Ask the 3-way question below, then route |
| Quality analyze | "quality check", "validate", "review workflow/skill" | Load references/quality-analysis.md |
| Unclear | — | Present options and ask |
Analyze routes to references/quality-analysis.md. Edit and Rebuild both route to references/build-process.md with the chosen intent.
Regardless of path, respect headless mode if requested.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
代码仓库 AI 亲和度审计工具，支持前端、后端、全栈等各类项目。此技能用于检查给定的代码仓库对 AI Coding 工具的友好程度，生成详细的分析报告和改进建议。当用户需要评估代码仓库是否适合 AI 辅助开发、希望提升仓库的 AI 可操作性、或准备引入 AI Coding 工具前进行仓库评估时，应使用此技能。支持 TypeScript/JavaScript、Go、Java/Kotlin、Python、Rust 等主流技术栈。融合 OpenAI Harness Engineering 方法论，评估 Outer Loop（反馈闭环、评估门禁、机械化不变量）建设。
日本語の概要は準備中です。原文の説明を表示しています。
OPC-Starter 智能开发技能。AI 亲和的 React Boilerplate 项目开发规范，支持动态上下文感知、TDD 驱动开发、Agent Studio 扩展。适用于认证系统、组织架构、Agent 工具、数据同步等模块的迭代开发。
日本語の概要は準備中です。原文の説明を表示しています。
Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.
日本語の概要は準備中です。原文の説明を表示しています。
Strategic business analyst and requirements expert. Use when the user asks to talk to Mary or requests the business analyst.
日本語の概要は準備中です。原文の説明を表示しています。
System architect and technical design leader. Use when the user asks to talk to Winston or requests the architect.
日本語の概要は準備中です。原文の説明を表示しています。
Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".
日本語の概要は準備中です。原文の説明を表示しています。