bmad-agent-builder

Build, edit, and analyze BMad agent skills from repository content.

Updated May 23, 2026
One-click install
npx skills add https://github.com/diegosanchespereira1/lavarapido --skill bmad-agent-builder-diegosanchespereira1
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bmad-agent-builder
Source: https://github.com/diegosanchespereira1/lavarapido/tree/main/lava-rapido/.agents/skills/bmad-agent-builder
Command: npx skills add https://github.com/diegosanchespereira1/lavarapido --skill bmad-agent-builder-diegosanchespereira1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

It turns vague agent ideas, existing agent bundles, and quality concerns into complete BMad Agent Skills with the right structure, routing, and onboarding flow.

Core Features & Use Cases

  • Conversational skill creation: Guides users from intent discovery to a finished agent skill.
  • Skill analysis and editing: Reviews existing agents, identifies quality issues, and supports targeted refactors.
  • Sanctum-aware building: Handles memory-agent scaffolding, First Breath onboarding, capability registration, and quality-report workflows.
  • Use Case: A developer can hand it a repository or an existing skill and get back a structured analysis or a rebuild plan for the agent.

Quick Start

Use the bmad-agent-builder skill to analyze the agent skill directory in this repository and generate a quality report.

Frequently Asked Questions about bmad-agent-builder

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

FAQPage Schema
How do I build an autonomous agent from repository content?

You can build an autonomous agent from repository content by using conversational skill creation to discover intent and generate a structured BMad agent skill with proper routing and onboarding scaffolding.

What is the best way to refactor existing agent skills?

Refactoring existing agent skills involves analyzing the current bundle to identify quality issues and then applying targeted edits to improve stateless, memory, or autonomous workflows.

How does agent skill quality analysis work for memory workflows?

Agent skill quality analysis for memory workflows works by evaluating the existing agent bundle against structural rules, generating a deterministic quality report that highlights areas for targeted refactors.

Can I use prompt engineering to scaffold a sanctum-aware agent?

Yes, you can use prompt engineering to scaffold a sanctum-aware agent by guiding the conversational creation process to handle memory-agent scaffolding and First Breath onboarding.

Do I need pyyaml to generate deterministic pre-pass scripts?

Yes, you need pyyaml installed to support the execution of deterministic pre-pass scripts and the underlying automation logic required during the agent skill building process.

When should I not use an automated agent builder for skill creation?

You should not use an automated agent builder when your workflow requires highly custom capability routing that falls outside standard frontmatter discovery and sanctum scaffolding constraints.