AGENT SKILL

gds-generate-project-context

Create optimized project-context.md for AI agent consistency. Use when the user says "project context" or "generate context"

License 许可
MIT
最近更新
2026-07-19
Stars
★ 1
Forks
0

01 前言 Front Matter

name
gds-generate-project-context
description
Create optimized project-context.md for AI agent consistency. Use when the user says "project context" or "generate context"

02 资源文件 5

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 game 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 game code generation across all AI agents working on the project.


Conventions

  • Bare paths (e.g. template.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.

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/gds/config.yaml and resolve:

  • user_name
  • communication_language
  • output_folder

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.

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.

Paths

  • installed_path = {skill_root}
  • template_path = {installed_path}/project-context-template.md
  • output_file = {output_folder}/project-context.md

EXECUTION

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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