bmad-generate-project-context — quality + safety report
In the Skillier index (bmad__bmad-generate-project-context) · scanned 2026-06-03 · engine: builtin+triage
✓ Clean — no heuristic safety flags surfaced.
Heuristic flags from the builtin scanner, which is known to over-flag (it trips on legitimate env-reading integrations, security skills, and library .eval calls). This is NOT an authoritative malicious verdict — re-scan with SkillSpector for the authoritative result. Run the authoritative scan →
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About this skill
Create project-context.md with AI rules. Use when the user says "generate project context" or "create project context"
📄 Read the SKILL.md
---
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"'
---
# 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. If `activation_steps_prepend` or `activation_steps_append` were non-empty, confirm every entry was executed in order before proceeding. Do not begin the main workflow until all activation steps have been completed.
## 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.Want a live grade + an embeddable README badge? Run your skill through the free scanner.
Graded independently by Skillproof — nothing to sell the author. Quality is mechanical + corpus-grounded; safety flags are heuristic (builtin+triage), not a malicious verdict.