AI Agent Architecture Designer
Design or audit an AI agent's architecture, with justified decisions and verification steps, without implementing it
- Repository
- github/awesome-copilot
- Stars
- 40,703
- Licence
- MIT
- Files
- 15 files
What it does
This skill makes an AI assistant act as an architect for AI agents. When you describe a task you want an agent to handle, it interviews you about requirements, then recommends an architecture: which components are needed, how the flow runs, where rules must be enforced in code rather than left to the model, and how to verify the design. If you already have an agent, it audits the existing design and diagnoses flaws such as mistakes, degradation, or false 'done' reports. It deliberately does not write the agent's code; it delivers decisions, assumptions and open questions, and by default a PDF report and a visualization.
Great for
- Teams planning a new AI agent who want to decide between a simple workflow, a single model call, or a full agent loop before building
- Developers reviewing an existing agent that makes mistakes, degrades over time, or reports tasks as finished when they are not
- Architects who want requirements, cost of failure, and verification methods written down before implementation
Skip it if
- Simple one-off prompts or tasks that plain automation or a single model call can handle, since the skill pushes toward minimal design and may add unnecessary process
- Actual code implementation or general code review, which the skill explicitly excludes; it hands off to other processes once an architecture is accepted
- Auditing a live production agent by running it, since the skill forbids running applications with external effects during an audit
Try asking
- “I want to build an agent that triages customer support emails. Help me decide the architecture before we code anything.”
- “Review our existing agent's design and find where it can make irreversible mistakes or falsely report success.”
- “Here is our agent specification; fill in the gaps and produce an architecture package with a PDF report.”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 15 original files, the MIT licence and an attribution note.
agent-architecture.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip agent-architecture.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip agent-architecture.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Describe the task, its cost of failure, and what systems the agent would touch, so the interview can start from real constraints.
- Provide existing specifications, local instructions, or code when you have them; the skill reconstructs architecture from these rather than asking everything again.
- Answer one decision at a time; the skill is built to handle one topic per turn and to label your answers as user requirements versus its own proposals.
What's inside
- agents/openai.yaml
- LICENSE.txt
- references/architecture-contract.md
- references/architecture-selection.md
- references/audit.md
- references/capability-design.md
- references/design.md
- references/diagnostic-review.md
- references/discovery-protocol.md
- references/evaluation-design.md
- references/execution-continuity.md
- references/result-delivery.md
- references/scenarios.md
- references/source-map.md
- SKILL.md
Redistributed unmodified from github/awesome-copilot under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.