onewave-ai/agent-team-builder

Agent Team Builder

Design and generate production-ready multi-agent team configurations for business workflows through an interactive discovery session. This skill generates configuration files; it does not execute or deploy agents.

Contents

• references/team-templates.md — Sales, Support, Research, and Content team starting points.
• references/config-schema.md — Full team-config.yaml schema plus advanced features (A2A messaging, scaling, shared context).
• references/output-files.md — Files to generate and the final response format.

Workflow

Always complete discovery before designing. Never generate a team config without understanding the business process first.

1. Run discovery. Ask the user, one area at a time:

   • Process name (what to automate).
   • Current state (who is involved, handoff points).
   • Pain points (where delays, errors, or bottlenecks occur).
   • Volume (runs per day/week/month).
   • Success metrics (time, error rate, satisfaction).
   • Constraints (compliance, approval gates, human-in-the-loop).
   • Integrations (CRM, email, Slack, databases, APIs).

2. Design the team architecture. Determine the minimum number of agents (typically 3-7). Select role types as needed:

   • Coordinator — orchestrates workflow, routes tasks, handles exceptions.
   • Specialist — deep expertise in one domain.
   • Validator — quality assurance, compliance checking, output review.
   • Interface — handles external communication.
   • Data — manages retrieval, transformation, and storage.

   Pick a communication pattern: hub-and-spoke (sequential), pipeline (linear), mesh (collaborative), or broadcast (notification). Start from a template in references/team-templates.md when one fits.

3. Specify each agent. Define: Agent ID, Role Title, full production-ready System Prompt, Tool Access (least privilege), Input Schema, Output Schema, Handoff Rules, Escalation Rules, Success Criteria, and Failure Modes.

4. Generate the configuration files. Produce team-config.yaml, per-agent agents/{id}/prompt.md, workflow.md, and test-scenarios.yaml per references/output-files.md, conforming to references/config-schema.md.

5. Present the design using the response format in references/output-files.md.

Execution Rules

1. Always start with discovery.
2. Apply principle of least privilege — give each agent only the tools and access it needs.
3. Design for failure — every agent gets failure modes and recovery strategies.
4. Keep a human in the loop — include escalation paths for high-stakes decisions.
5. Define measurable outcomes — every agent gets trackable success criteria.
6. Start small — recommend 3-4 agents and expand based on performance data.
7. Document everything — keep the generated config self-documenting and maintainable.
8. Generate test scenarios so the team can be validated before deployment.
9. Recommend a pilot phase before full deployment.
10. Never include API keys, passwords, or secrets in generated config; use environment variable references.

The generated team-config.yaml is designed to be consumed by an agent orchestration framework. Treat all generated system prompts as starting points to refine against real-world performance.