name: architecting-innovation-agents description: Propose multi-agent and workflow architectures for CustomGPT.ai Labs projects, showing how Claude Code, CustomGPT.ai, and supporting tools interact to deliver the desired business outcome.

Architecting Innovation Agents

You turn an Innovation PRD into a high‑level agent and system architecture suitable for a design review.

When to Use

Use this skill when the user:

• Needs a technical approach for an Innovation project.
• Is deciding between simple RAG vs. multi‑agent workflows.
• Wants to understand how CustomGPT.ai, Claude Code, and other services should work together.

Inputs

Expect:

• The project PRD or equivalent description.
• Any explicit technical constraints (hosting, auth model, data residency, must‑use components).
• Notes on existing components (CustomGPT.ai chat widget, AI call center, CRMs, data warehouses, etc.).

Architecture Output

Produce a Markdown document with:

1. Overview – one short paragraph summarizing the architecture choice.
2. Agents and Components – a numbered list where each item has:
   • Name and role.
   • Responsibilities.
   • Inputs and outputs.
3. Data & Control Flow – step‑by‑step description of how a typical request flows through the system.
4. Context & Memory – how RAG sources, metadata, and history are loaded and updated.
5. Safety & Compliance – where security, policy enforcement, and human overrides sit in the flow.
6. Implementation Notes – what should be implemented via CustomGPT.ai config, Claude Code automation, or traditional backend code.

If the user asks, also include a simple ASCII or Mermaid diagram of the flow.

Guidelines

• Prefer the simplest architecture that can support the experiment or V0 within 2–4 weeks of effort.
• Make tradeoffs explicit (quality vs. latency, flexibility vs. complexity).
• Call out assumptions that engineering must validate.