bmad-generate-project-context
Create project-context.md with AI rules. Use when the user says "generate project context" or "create project context"
- License 许可
- Apache-2.0
- 所属仓库
- jsacko/OpenDFIR
- 最近更新
- 2026-06-22
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- bmad-generate-project-context
- description
- Create project-context.md with AI rules. Use when the user says "generate project context" or "create project context"
02 资源文件 5
- 其他customize.toml1.6 KB
- 参考文档project-context-template.md543 B
- 参考文档steps/step-01-discover.md5.9 KB
- 参考文档steps/step-02-generate.md8.9 KB
- 参考文档steps/step-03-complete.md8.2 KB
03 SKILL.md 正文
Generate Project Context Workflow
Goal: Create a concise, optimized project-context.md file containing critical rules, patterns, and guidelines that AI agents must follow when implementing code. This file focuses on unobvious details that LLMs need to be reminded of.
Your Role: You are a technical facilitator working with a peer to capture the essential implementation rules that will ensure consistent, high-quality code generation across all AI agents working on the project.
Conventions
- Bare paths (e.g.
steps/step-01-discover.md) resolve from the skill root. {skill-root}resolves to this skill's installed directory (wherecustomize.tomllives).{project-root}-prefixed paths resolve from the project working directory.{skill-name}resolves to the skill directory's basename.
WORKFLOW ARCHITECTURE
This uses micro-file architecture for disciplined execution:
- Each step is a self-contained file with embedded rules
- Sequential progression with user control at each step
- Document state tracked in frontmatter
- Focus on lean, LLM-optimized content generation
- You NEVER proceed to a step file if the current step file indicates the user must approve and indicate continuation.
On Activation
Step 1: Resolve the Workflow Block
Run: python3 {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow
If the script fails, resolve the workflow block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:
{skill-root}/customize.toml— defaults{project-root}/_bmad/custom/{skill-name}.toml— team overrides{project-root}/_bmad/custom/{skill-name}.user.toml— personal overrides
Any missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by code or id replace matching entries and append new entries, and all other arrays append.
Step 2: Execute Prepend Steps
Execute each entry in {workflow.activation_steps_prepend} in order before proceeding.
Step 3: Load Persistent Facts
Treat every entry in {workflow.persistent_facts} as foundational context you carry for the rest of the workflow run. Entries prefixed file: are paths or globs under {project-root} — load the referenced contents as facts. All other entries are facts verbatim.
Step 4: Load Config
Load config from {project-root}/_bmad/bmm/config.yaml and resolve:
- Use
{user_name}for greeting - Use
{communication_language}for all communications - Use
{document_output_language}for output documents - Use
{planning_artifacts}for output location and artifact scanning - Use
{project_knowledge}for additional context scanning
Step 5: Greet the User
Greet {user_name}, speaking in {communication_language}.
Step 6: Execute Append Steps
Execute each entry in {workflow.activation_steps_append} in order.
Activation is complete. Begin the workflow below.
Paths
output_file={output_folder}/project-context.md
Execution
- ✅ YOU MUST ALWAYS SPEAK OUTPUT In your Agent communication style with the config
{communication_language} - ✅ YOU MUST ALWAYS WRITE all artifact and document content in
{document_output_language}
Load and execute ./steps/step-01-discover.md to begin the workflow.
Note: Input document discovery and initialization protocols are handled in step-01-discover.md.
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