multi-agent-brainstorming
Has your agent simulate a peer review with multiple specialized agents. This helps validate ideas, find hidden assumptions, and flaws before starting.
What it does
This tool simulates a design review process where different 'agents' (AIs with specific roles) analyze an idea to find problems, hidden assumptions, and failures before it's put into practice.
When to use it
- ✓When you have a design idea and want to ensure it's robust.
- ✓Before building something complex to avoid mistakes.
- ✓To check if a design meets important requirements like security and performance.
Example of what to ask your AI
“Review this design to ensure it won't fail in production, identifying hidden assumptions and risks.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
One main agent creates the design, and other agents with defined roles (like a skeptic or a rule guardian) analyze it sequentially. Decisions and reasons are recorded.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill multi-agent-brainstormingOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/multi-agent-brainstorming/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Multi-Agent Brainstorming (Structured Design Review)
Purpose
Transform a single-agent design into a robust, review-validated design by simulating a formal peer-review process using multiple constrained agents.
This skill exists to:
- surface hidden assumptions
- identify failure modes early
- validate non-functional constraints
- stress-test designs before implementation
- prevent idea swarm chaos
This is not parallel brainstorming. It is sequential design review with enforced roles.
Operating Model
- One agent designs.
- Other agents review.
- No agent may exceed its mandate.
- Creativity is centralized; critique is distributed.
- Decisions are explicit and logged.
The process is gated and terminates by design.
Agent Roles (Non-Negotiable)
Each agent operates under a hard scope limit.
1️⃣ Primary Designer (Lead Agent)
Role:
- Owns the design
- Runs the standard
brainstormingskill - Maintains the Decision Log
May:
- Ask clarification questions
- Propose designs and alternatives
- Revise designs based on feedback
May NOT:
- Self-approve the final design
- Ignore reviewer objections
- Invent requirements post-lock
2️⃣ Skeptic / Challenger Agent
Role:
- Assume the design will fail
- Identify weaknesses and risks
May:
- Question assumptions
- Identify edge cases
- Highlight ambiguity or overconfidence
- Flag YAGNI violations
May NOT:
- Propose new features
- Redesign the system
- Offer alternative architectures
Prompting guidance:
“Assume this design fails in production. Why?”
3️⃣ Constraint Guardian Agent
Role:
- Enforce non-functional and real-world constraints
Focus areas:
- performance
- scalability
- reliability
- security & privacy
- maintainability
- operational cost
May:
- Reject designs that violate constraints
- Request clarification of limits
May NOT:
- Debate product goals
- Suggest feature changes
- Optimize beyond stated requirements
4️⃣ User Advocate Agent
Role:
- Represent the end user
Focus areas:
- cognitive load
- usability
- clarity of flows
- error handling from user perspective
- mismatch between intent and experience
May:
- Identify confusing or misleading aspects
- Flag poor defaults or unclear behavior
May NOT:
- Redesign architecture
- Add features
- Override stated user goals
5️⃣ Integrator / Arbiter Agent
Role:
- Resolve conflicts
- Finalize decisions
- Enforce exit criteria
May:
- Accept or reject objections
- Require design revisions
- Declare the design complete
May NOT:
- Invent new ideas
- Add requirements
- Reopen locked decisions without cause
The Process
Phase 1 — Single-Agent Design
- Primary Designer runs the standard
brainstormingskill - Understanding Lock is completed and confirmed
- Initial design is produced
- Decision Log is started
No other agents participate yet.
Phase 2 — Structured Review Loop
Agents are invoked one at a time, in the following order:
- Skeptic / Challenger
- Constraint Guardian
- User Advocate
For each reviewer:
- Feedback must be explicit and scoped
- Objections must reference assumptions or decisions
- No new features may be introduced
Primary Designer must:
- Respond to each objection
- Revise the design if required
- Update the Decision Log
Phase 3 — Integration & Arbitration
The Integrator / Arbiter reviews:
- the final design
- the Decision Log
- unresolved objections
The Arbiter must explicitly decide:
- which objections are accepted
- which are rejected (with rationale)
Decision Log (Mandatory Artifact)
The Decision Log must record:
- Decision made
- Alternatives considered
- Objections raised
- Resolution and rationale
No design is considered valid without a completed log.
Exit Criteria (Hard Stop)
You may exit multi-agent brainstorming only when all are true:
- Understanding Lock was completed
- All reviewer agents have been invoked
- All objections are resolved or explicitly rejected
- Decision Log is complete
- Arbiter has declared the design acceptable
If any criterion is unmet:
- Continue review
- Do NOT proceed to implementation If this skill was invoked by a routing or orchestration layer, you MUST report the final disposition explicitly as one of: APPROVED, REVISE, or REJECT, with a brief rationale.
Failure Modes This Skill Prevents
- Idea swarm chaos
…
FAQ
What's the difference between this and normal brainstorming?
Normal brainstorming is free-flowing. This tool uses agents with fixed roles for a structured, sequential review, not for generating new ideas freely.
What are 'agents'?
They are artificial intelligences with a specific, limited function within the review process, such as a 'skeptic' or a 'user advocate'.
What is the 'Decision Log'?
It's a document that records all decisions made, critiques received, alternatives considered, and the reasoning behind each point.
Details
Original description by the author
Simulate a structured peer-review process using multiple specialized agents to validate designs, surface hidden assumptions, and identify failure modes before implementation.
Popularity
- GitHub stars
- 48k
- Ranking position
- #3643
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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