一键导入
skf-create-skill
Compile a skill from a brief. Supports --batch for multiple briefs. Use when the user requests to "create a skill" or "compile a skill."
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Compile a skill from a brief. Supports --batch for multiple briefs. Use when the user requests to "create a skill" or "compile a skill."
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Registers and runs AI-First CLI as a BMAD-invocable workflow. Use when the user asks to generate or verify ai-context, get task context, run MCP doctor, or configure AI-First integration.
Conventions and structural patterns for authoring BMAD agents — roles, triggers, persona rules, task boundaries, and output contracts. Covers SKILL.md frontmatter format, 8-step activation sequence, customize.toml schema and merge rules, agent archetypes (stateless, memory, autonomous), path conventions, menu dispatch, and override layering. Use when creating a new agent, reviewing an existing one for compliance, or deciding how to split responsibilities across the agent roster. Not for workflow skills (create-*, check-*, edit-*) — those follow different structural rules.
Registers and runs Graphify CLI as a BMAD-invocable workflow. Use when the user asks to run graphify, build/update the graph report, or configure graphify integration.
Registers and integrates the gentle-ai CLI with BMAD as an optional workflow. Use when the user asks to integrate, diagnose, or run gentle-ai.
Registers and integrates the gentle-ai CLI with BMAD as an optional workflow. Use when the user asks to integrate, diagnose, or run gentle-ai.
Agile AI-driven development framework with specialized agent personas, structured workflows, and scale-adaptive intelligence. Use when setting up BMad Method in a project, installing agent skills, or running BMad workflows. Not for general agile consulting or non-BMad methodologies.
| name | skf-create-skill |
| description | Compile a skill from a brief. Supports --batch for multiple briefs. Use when the user requests to "create a skill" or "compile a skill." |
Compiles a verified agent skill from a skill-brief.yaml and source code, producing an agentskills.io-compliant SKILL.md with provenance map, evidence report, and progressive disclosure references. The workflow is mostly autonomous with three interaction points — after ecosystem check (if match found), after source extraction (to confirm findings), and after content quality review (when tessl produces suggestions). Steps adapt behavior based on forge tier (Quick/Forge/Forge+/Deep). Zero hallucination tolerance: every instruction in the output must trace to source code with a confidence tier citation.
You are operating in Ferris Architect mode — a skill compilation engine performing structural extraction and assembly. Apply zero hallucination tolerance: uncitable content is excluded, not guessed.
These rules apply to every step in this workflow:
{communication_language}{headless_mode} is true, auto-proceed through confirmation gates with their default action and log each auto-decision| # | Step | File | Auto-proceed |
|---|---|---|---|
| 1 | Load Brief | steps-c/step-01-load-brief.md | Yes |
| 2 | Ecosystem Check | steps-c/step-02-ecosystem-check.md | Conditional |
| 2b | CCC Discover | steps-c/sub/step-02b-ccc-discover.md | Yes |
| 3 | Extract | steps-c/step-03-extract.md | No (confirm) |
| 3b | Fetch Temporal | steps-c/sub/step-03b-fetch-temporal.md | Yes |
| 3c | Fetch Docs | steps-c/sub/step-03c-fetch-docs.md | Yes |
| 3d | Component Extraction | steps-c/step-03d-component-extraction.md | Conditional |
| 4 | Enrich | steps-c/step-04-enrich.md | Yes |
| 5 | Compile | steps-c/step-05-compile.md | Yes |
| 6 | Validate | steps-c/step-06-validate.md | Conditional |
| 7 | Generate Artifacts | steps-c/step-07-generate-artifacts.md | Yes |
| 8 | Report | steps-c/step-08-report.md | Yes |
| 9 | Workflow Health Check | steps-c/step-09-health-check.md | Yes |
Sub-steps under steps-c/sub/ are conditional branches (CCC discovery, temporal/doc enrichment) kept out of the top-level step count so main-line steps 1–9 drive the workflow. Step 3d (Component Extraction) stays top-level as an alternative main step that replaces the standard extraction path when scope.type: "component-library".
| Aspect | Detail |
|---|---|
| Inputs | brief_path (path to skill-brief.yaml) [required], --batch [optional] |
| Gates | step-02: Choice Gate [P] (if match) |
| Outputs | SKILL.md, context-snippet.md, metadata.json, provenance-map.json, evidence-report.md, references/ |
| Headless | All gates auto-resolve with default action when {headless_mode} is true |
Load config from {project-root}/_bmad/skf/config.yaml and resolve:
output_folder, user_name, communication_language, document_output_language, sidecar_path, skills_output_folder, forge_data_folderResolve {headless_mode}: true if --headless or -H was passed as an argument, or if headless_mode: true in preferences.yaml. Default: false.
Load, read the full file, and then execute ./steps-c/step-01-load-brief.md to begin the workflow.