architecting-innovation-agents
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.
Best use case
architecting-innovation-agents is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using architecting-innovation-agents should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/architecting-innovation-agents/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How architecting-innovation-agents Compares
| Feature / Agent | architecting-innovation-agents | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# 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.
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