Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

Back to skills

Antigravity Multi Agent Brainstorming

ASecurity

Simulate a structured peer-review process using multiple specialized agents to validate designs, surface hidden assumptions, and identify failure modes before implementation.

2 stars
0 votes
0 copies
0 views
Added 9/19/2026
ai-agentsgosecurityperformance

Security Analysis

A100/100

Scanned 9/19/2026

Install to Claude Code

$npx -y skills add ibragimov-oasis/oasis-languages-jp --skill antigravity-multi-agent-brainstorming --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Antigravity Multi Agent Brainstorming?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Antigravity Multi Agent Brainstorming
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/ibragimov-oasis-antigravity-multi-agent-brainstorming/badge)](https://www.skillsdirectory.com/skills/ibragimov-oasis-antigravity-multi-agent-brainstorming)

More formats (shields.io, HTML) on the badges page.

Download Zip
Files
SKILL.md
---
name: multi-agent-brainstorming
description: "Simulate a structured peer-review process using multiple specialized agents to validate designs, surface hidden assumptions, and identify failure modes before implementation."
risk: unknown
source: community
date_added: "2026-02-27"
tags:
  - domain/skills
  - artifact/skill
  - source/skills-antigravity
---

# 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 `brainstorming` skill
- 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

1. Primary Designer runs the **standard `brainstorming` skill**
2. Understanding Lock is completed and confirmed
3. Initial design is produced
4. 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:

1. Skeptic / Challenger
2. Constraint Guardian
3. 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
- Hallucinated consensus
- Overconfident single-agent designs
- Hidden assumptions
- Premature implementation
- Endless debate

---

## Key Principles

- One designer, many reviewers
- Creativity is centralized
- Critique is constrained
- Decisions are explicit
- Process must terminate

---

## Final Reminder

This skill exists to answer one question with confidence:

> “If this design fails, did we do everything reasonable to catch it early?”

If the answer is unclear, **do not exit this skill**.

## When to Use
This skill is applicable to execute the workflow or actions described in the overview.

## 🔗 Связи

- [[MOC - Skills]] — Skills library
- [[skills/skills-antigravity]] — Category: skills-antigravity

Attribution

ibragimov-oasisibragimov-oasis
View sourceMore from ibragimov-oasis →
SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Related Skills

Caveman

Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.

1023331 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

686011 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3331 votes

catchup

Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.

611 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →