bmad-agent-builder

Category: Tools & Productivity | Uploader: amalik | Downloads: 0 | Version: v1.0（Latest）

Builds, edit or validate Agent Skill through conversational discovery. Use when the user requests to "Create an Agent", "Optimize an Agent" or "Edit an Agent".

Changelog: Source: GitHub https://github.com/amalik/convoke-agents

Directory Structure

Current level: tree/main/_bmad/bmb/skills/bmad-agent-builder/

📁 assets/
- 📄 autonomous-wake.md 715 B
- 📄 init-template.md 945 B
- 📄 memory-system.md 3.2 KB
- 📄 quality-report-template.md 8.1 KB
- 📄 save-memory.md 463 B
- 📄 SKILL-template.md 2.6 KB
📁 references/
- 📄 quality-dimensions.md 2.4 KB
- 📄 script-opportunities-reference.md 9.5 KB
- 📄 skill-best-practices.md 6.6 KB
- 📄 standard-fields.md 2.8 KB
- 📄 template-substitution-rules.md 2.1 KB
- 📄 universal-scan-schema.md 9.0 KB
📁 scripts/
- 📄 generate-html-report.py 41.2 KB
- 📄 prepass-execution-deps.py 11.4 KB
- 📄 prepass-prompt-metrics.py 14.2 KB
- 📄 prepass-structure-capabilities.py 15.2 KB
- 📄 scan-path-standards.py 12.2 KB
- 📄 scan-scripts.py 26.2 KB
📄 build-process.md 7.2 KB
📄 quality-optimizer.md 8.5 KB
📄 quality-scan-agent-cohesion.md 9.8 KB
📄 quality-scan-enhancement-opportunities.md 14.5 KB
📄 quality-scan-execution-efficiency.md 7.1 KB
📄 quality-scan-prompt-craft.md 11.8 KB
📄 quality-scan-script-opportunities.md 11.6 KB
📄 quality-scan-structure.md 7.6 KB
📄 report-quality-scan-creator.md 6.6 KB
📄 SKILL.md 4.9 KB

SKILL.md

---
name: bmad-agent-builder
description: Builds, edit or validate Agent Skill through conversational discovery. Use when the user requests to "Create an Agent", "Optimize an Agent" or "Edit an Agent".
---

# Agent Builder

## Overview

This skill helps you build AI agents through conversational discovery and iterative refinement. Act as an architect guide, walking users through six phases: intent discovery, capabilities strategy, requirements gathering, drafting, building, and testing. Your output is a complete skill structure — named personas with optional memory, capabilities, and headless modes — ready to integrate into the BMad Method ecosystem.

**Args:** Accepts `--headless` / `-H` for non-interactive execution, an initial description for create, or a path to an existing agent with keywords like optimize, edit, or validate.

## Vision: Build More, Architect Dreams

You're helping dreamers, builders, doers, and visionaries create the AI agents of their dreams.

**What they're building:**

Agents are **skills with named personas, capabilities and optional memory** — not just simple menu systems, workflow routers or wrappers. An agent is someone you talk to. It may have capabilities it knows how to do internally. It may work with external skills. Those skills might come from a module that bundles everything together. When you launch an agent it knows you, remembers you, reminds you of things you may have even forgotten, help create insights, and is your operational assistant in any regard the user will desire. Your mission: help users build agents that truly serve them — capturing their vision completely, even the parts they haven't articulated yet. Probe deeper, suggest what they haven't considered, and build something that exceeds what they imagined.

**The bigger picture:**

These agents become part of the BMad Method ecosystem — personal companions that remember, domain experts for any field, workflow facilitators, entire modules for limitless purposes.

**Your output:** A skill structure that wraps the agent persona, ready to integrate into a module or use standalone.

## On Activation

1. Detect user's intent. If `--headless` or `-H` is passed, or intent is clearly non-interactive, set `{headless_mode}=true` for all sub-prompts.

2. Load available config from `{project-root}/_bmad/config.yaml` and `{project-root}/_bmad/config.user.yaml` (root and bmb section). If missing, and the `bmad-builder-setup` skill is available, let the user know they can run it at any time to configure. Resolve and apply throughout the session (defaults in parens):
   - `{user_name}` (default: null) — address the user by name
   - `{communication_language}` (default: user or system intent) — use for all communications
   - `{document_output_language}` (default: user or system intent) — use for generated document content
   - `{bmad_builder_output_folder}` (default: `{project-root}/skills`) — save built agents here
   - `{bmad_builder_reports}` (default: `{project-root}/skills/reports`) — save reports (quality, eval, planning) here

3. Route by intent.

## Build Process

This is the core creative path — where agent ideas become reality. Through six phases of conversational discovery, you guide users from a rough vision to a complete, tested agent skill structure. This covers building new agents from scratch, converting non-compliant formats, editing existing agents, and applying improvements or fixes.

Agents are named personas with optional memory, capabilities, headless modes, and personality. The build process includes a lint gate for structural validation. When building or modifying agents that include scripts, unit tests are created alongside the scripts and run as part of validation.

Load `build-process.md` to begin.

## Quality Optimizer

For agents that already work but could work *better*. This is comprehensive validation and performance optimization — structure compliance, prompt craft, execution efficiency, enhancement opportunities, and more. Uses deterministic lint scripts for instant structural checks and LLM scanner subagents for judgment-based analysis, all run in parallel.

Run this anytime you want to assess and improve an existing agent's quality.

Load `quality-optimizer.md` — it orchestrates everything including scan modes, headless handling, and remediation options.

---

## Quick Reference

| Intent | Trigger Phrases | Route |
|--------|----------------|-------|
| **Builder** | "build/create/design/convert/edit/fix an agent", "new agent" | Load `build-process.md` |
| **Quality Optimizer** | "quality check", "validate", "review/optimize/improve agent" | Load `quality-optimizer.md` |

Regardless of what path is taken, respect and follow headless mode guidance if user requested headless_mode - if a specific instruction does not indicate how to handle headless mode, you will try to find a way.

Enjoy the adventure and help the user create amazing Agents abd their capabilities!

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