bmad-generate-project-context

Generate project-context.md by discovering repository technology stack and implementation rules.

4|Updated Apr 26, 2026
One-click install
npx skills add https://github.com/curdx/curdx-flow --skill bmad-generate-project-context-curdx
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bmad-generate-project-context
Source: https://github.com/curdx/curdx-flow/tree/main/.agents/skills/bmad-generate-project-context
Command: npx skills add https://github.com/curdx/curdx-flow --skill bmad-generate-project-context-curdx

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps teams produce a concise, high-signal project-context document that prevents AI agents from drifting on architecture, conventions, and implementation rules.

Core Features & Use Cases

  • Generates project-context.md from repo evidence: Discovers the technology stack (with versions), existing patterns, and critical “don’t-miss” rules by scanning the repository.
  • Collaborative, stepwise rule capture: Guides the user through discovery and then iteratively builds rule categories with explicit A/P/C validation.
  • Optimized for agent consumption: Produces a lean, LLM-friendly rules file with tracked completion sections and clear usage boundaries.

Quick Start

Use the bmad-generate-project-context skill to create project-context.md by saying “generate project context” in your project workflow.

Frequently Asked Questions about bmad-generate-project-context

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate project context rules for LLM agents?▼

Generating project context involves scanning your repository to discover the technology stack and existing patterns, then collaboratively capturing implementation rules to output a structured project-context.md file optimized for LLM consumption.

What is a project context file used for in spec-driven agent workflows?▼

A project-context.md file provides persistent, restart-safe guidance for spec-driven agent workflows, ensuring consistent code generation by preventing AI agents from drifting on architecture, conventions, and implementation rules across multiple agents.

How do I ensure my AI coding agents follow existing repository patterns?▼

You ensure agents follow existing patterns by using a guided discovery process that scans the repository for established technology stacks and conventions, then iteratively captures these rules with enforced step gating and user approval.

Does generating an LLM-ready project context require manual rule input?▼

Generating project context requires collaborative, stepwise rule capture where the user validates discovered patterns, ensuring no rule categories proceed without explicit user approval and enforced step gating.

Can I use automated documentation discovery for multi-agent code generation?▼

Automated documentation discovery applies to multi-agent code generation by producing a lean, LLM-friendly rules file that provides tracked completion sections and clear usage boundaries for consistent guidance across agents.