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 (where

  customize.toml

  lives).

• {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:

1. {skill-root}/customize.toml

   — defaults

2. {project-root}/_bmad/custom/{skill-name}.toml

   — team overrides

3. {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.