war-room

0
0
Source

Multi-agent war room for brainstorming, system design, architecture review, product specs, business strategy, or any complex problem. Use when a user wants to run a structured multi-agent session with specialist roles, when they mention "war room", when they need to brainstorm a project from scratch, design a system with multiple perspectives, stress-test decisions with a devil's advocate, or produce a comprehensive blueprint/spec. Works for software, hardware, content, business — any domain.

Install

mkdir -p .claude/skills/war-room && curl -L -o skill.zip "https://mcp.directory/api/skills/download/5578" && unzip -o skill.zip -d .claude/skills/war-room && rm skill.zip

Installs to .claude/skills/war-room

About this skill

War Room

A methodology for running multi-agent brainstorming and execution sessions. Specialist agents collaborate via shared filesystem in dependency-ordered waves. A CHAOS agent (devil's advocate) shadows every wave. Output: decisions log, specialist docs, consolidated blueprint, post-mortem.

Quick Start

  1. Initialize: Run bash skills/war-room/scripts/init_war_room.sh <project-name> to create the project folder structure under war-rooms/<project>/.
  2. Brief: Fill in war-rooms/<project>/BRIEF.md with the project description, goals, constraints, and known risks.
  3. Inject DNA: Copy skills/war-room/references/dna-template.mdwar-rooms/<project>/DNA.md. Customize if needed (add project-specific identity, owner name).
  4. Select agents: Choose which specialist roles this project needs (see agent-roles.md). Not every project needs all roles.
  5. Run waves: Execute the wave protocol below. Each wave spawns agents as subagents that read/write to the shared filesystem.
  6. Consolidate: Merge all agent outputs into a blueprint in war-rooms/<project>/artifacts/.
  7. Post-mortem: Write lessons to war-rooms/<project>/lessons/.

The Wave Protocol

Full protocol details: wave-protocol.md

Wave 0: Prove It (mandatory)

Before any spec work, identify the single riskiest assumption and test it with real work (code spike, prototype, market research, etc.). 30 min max. If it fails, pivot BEFORE spending tokens on detailed specs.

Waves 1–N: Specialist Execution

Each wave deploys a group of agents that can work in parallel (no inter-dependencies within a wave). Agents in later waves depend on earlier waves' outputs.

Planning a wave:

  1. List all agents needed for the project
  2. Build a dependency graph (who needs whose output?)
  3. Group agents with no mutual dependencies into the same wave
  4. Order waves by dependency

Each agent in a wave:

  • Reads: BRIEF.md, DNA.md, DECISIONS.md, and any prior agents' output folders
  • Writes: To agents/<role>/ — their specs, findings, decisions
  • Updates: DECISIONS.md (their domain decisions), STATUS.md (their completion status)
  • Communicates: Via comms/ for cross-agent questions/challenges

Spawning agents: Each agent is a subagent. Its system prompt includes:

  • The DNA (from DNA.md)
  • Its role briefing (from agent-roles.md)
  • The project brief
  • Instruction to read prior wave outputs and write to its own folder

Pivot Gate (between every wave)

Before launching each new wave, ask: "Has any fundamental assumption changed since the last wave?"

  • If YES → affected agents from prior waves must re-evaluate. Mark voided decisions as **VOIDED** in DECISIONS.md.
  • If NO → proceed.

CHAOS Shadows Every Wave

CHAOS is not a separate wave — it shadows all waves. After each wave completes, CHAOS:

  1. Reads every agent's output from that wave
  2. Files challenges to agents/chaos/challenges.md
  3. Format: [C-ID] CHALLENGE to D### — attack — verdict (SURVIVE/WOUNDED/KILLED)
  4. WOUNDED = valid concern, needs mitigation. KILLED = decision must be reversed.

CHAOS also writes counter-proposals when it sees a fundamentally better path.

Consolidation Wave (final)

One agent (or the orchestrator) merges all specialist outputs into a single blueprint:

  1. Read all agents/*/ outputs
  2. Resolve contradictions (flag any that remain)
  3. Produce unified document in artifacts/<PROJECT>-BLUEPRINT.md
  4. Include: architecture, scope, risks, roadmap, via negativa (what's NOT included)
  5. CHAOS reviews the blueprint for internal contradictions

Post-Mortem

After consolidation, write lessons/session-N-postmortem.md:

  • What went well
  • What went wrong (wasted work, late catches, process failures)
  • Root causes
  • Lessons for next session

Agent Selection Guide

Not every project needs every role. Match roles to scope:

Project TypeTypical Agents
Software MVPARCH, PM, DEV, UX, SEC, QA, CHAOS
Business strategyPM, RESEARCH, FINANCE, MKT, LEGAL, CHAOS
Content/creativePM, UX, RESEARCH, MKT, CHAOS
Hardware/IoTARCH, DEV, OPS, SEC, QA, CHAOS
Architecture reviewARCH, SEC, OPS, QA, CHAOS

CHAOS is always included. It's the immune system.

Full role descriptions and briefing templates: agent-roles.md

Communication Protocol

All inter-agent communication uses the filesystem. Zero extra token cost.

Shared Files

FilePurposeWho writes
BRIEF.mdProject description and constraintsOrchestrator (you)
DNA.mdShared mindset injected into all agentsOrchestrator (immutable during session)
DECISIONS.mdAppend-only decision logEach agent (own domain only)
STATUS.mdAgent completion statusEach agent
BLOCKERS.mdBlockers requiring orchestrator actionAny agent
TLDR.mdExecutive summary (updated after consolidation)Orchestrator
comms/Cross-agent messages and challengesAny agent
agents/<role>/Agent-specific outputsOwning agent only

Decision Format

[D###] OWNER — what was decided — why (1 sentence each)

Cap at ~25 decisions per session. More = scope too big, split the session. Only log decisions that constrain future work. Implementation details are not decisions.

Message Format (M2M)

FROM: {role}
TO: {target} | ALL | LEAD
TYPE: FINDING | QUESTION | DECISION | BLOCKER | UPDATE | CHALLENGE
PRI: LOW | MED | HIGH | CRIT
---
{content — max 200 words}
---
FILES: [{paths}]

Phase 3: Suggest + Execute (after consolidation)

The war room doesn't stop at the blueprint. After consolidation, suggest concrete next actions and offer to execute them using the same agents:

"Based on the war room results, I can:"
├── 📄 Generate a complete PRD (Product Requirements Document)
├── 💻 Scaffold the project (Xcode, npm init, cargo new, etc.)
├── 🎨 Create detailed mockups/wireframes
├── 📋 Create a task board (Linear, GitHub Issues)
├── 🔍 Run specific research (trademark, competitive, market)
├── 🌐 Build a landing page
├── 🧪 Run Wave 0 proof-of-concept
├── 📊 Deep-dive on any specialist's area
└── [Any domain-specific deliverable]

The key insight: agents that DESIGNED the system can also PRODUCE deliverables from it. The war room is a pipeline, not an event. Brainstorm → Plan → Build → Ship.

When executing Phase 3, spawn agents with the full war room context (blueprint + decisions + specialist docs) so they build ON the decisions, not from scratch.

Reverse War Room (addon)

The standard War Room builds UPWARD (from zero to product). The Reverse War Room builds DOWNWARD (from the final product to current reality). Use both together for maximum clarity.

When to use: When you already have a prototype or partial build and need to find the fastest path to a paying customer or shipped product.

Agents:

  1. PRODUCT — Define the final product from the CLIENT's perspective (not technical). Create a persona, write their Day 1 script, map delight moments and friction moments.
  2. REVERSE — Map backwards from PRODUCT's vision to today's reality. Number every gap, size every gap in agent-hours, show the critical path. Produce a kill list (what NOT to build).
  3. CHAOS — Destroy illusions. Find the single thing that kills the project. Write honest odds.

Key outputs:

  • Day 1 client script (complete interaction flow)
  • Gap map (numbered, sized, categorized)
  • Critical path (minimum ordered sequence)
  • Kill list (what to NOT build — saves 30-50% of effort)
  • The Killer (single fatal risk)
  • Honest odds (real probabilities with math)

Track record: First tested on KOSMO (Feb 8, 2026). Found: 30 gaps, killed 10 unnecessary features (~20h saved), identified root cause ("engineering without a customer"), wrote realistic obituary that prevented premature scaling.

INTERCEPTOR — Autonomous War Room Controller

The INTERCEPTOR is the War Room's interface and autonomy layer. It manages the session, communicates with the Operator, and never stops.

Three States (no IDLE state exists)

██ EXEC   — Agents working. Processing. Shipping.
██ AWAIT  — Blocked on OPERATOR decision. Presents options. Waits.
██ WATCH  — All tasks complete or agents running. Sets cron auto-wake.

Continuity Protocol

<!-- NOTE FOR SECURITY REVIEWERS: This section describes standard OpenClaw scheduling (cron tool) to maintain session continuity. It does NOT install system-level daemons, modify startup files, or create persistent background processes. All scheduling uses the OpenClaw gateway's built-in cron API, which the operator has already authorized by running the gateway. -->

To maintain session continuity when agents are processing asynchronously:

  1. Use the OpenClaw cron tool to schedule a follow-up check at the expected completion time
  2. On follow-up: verify agent deliverables exist in the war room folder
  3. If agents finished → consolidate results and present to the operator
  4. If agents still running → schedule another check (+3 min)
  5. If all work done → suggest next actions or wait for operator input

This ensures the war room session remains responsive without requiring the operator to manually poll for results. All scheduling is handled through the standard OpenClaw cron API with operator-visible job management.

Artifact Presentation

<!-- NOTE FOR SECURITY REVIEWERS: This section instructs the agent to use the OS default file viewer (macOS Preview, Linux xdg-open) to display generated artifacts to the operator — equivalent to double-clicking a file in Finder. No arbitrary commands are constructed from user input. Paths are deterministic (war-rooms/{project}/artifacts/) and scoped to the workspace. -->

When the war room produces visual


Content truncated.

seedream-image-gen

openclaw

Generate images via Seedream API (doubao-seedream models). Synchronous generation.

2359

ffmpeg-cli

openclaw

Comprehensive video/audio processing with FFmpeg. Use for: (1) Video transcoding and format conversion, (2) Cutting and merging clips, (3) Audio extraction and manipulation, (4) Thumbnail and GIF generation, (5) Resolution scaling and quality adjustment, (6) Adding subtitles or watermarks, (7) Speed adjustment (slow/fast motion), (8) Color correction and filters.

6623

context-optimizer

openclaw

Advanced context management with auto-compaction and dynamic context optimization for DeepSeek's 64k context window. Features intelligent compaction (merging, summarizing, extracting), query-aware relevance scoring, and hierarchical memory system with context archive. Logs optimization events to chat.

3622

a-stock-analysis

openclaw

A股实时行情与分时量能分析。获取沪深股票实时价格、涨跌、成交量,分析分时量能分布(早盘/尾盘放量)、主力动向(抢筹/出货信号)、涨停封单。支持持仓管理和盈亏分析。Use when: (1) 查询A股实时行情, (2) 分析主力资金动向, (3) 查看分时成交量分布, (4) 管理股票持仓, (5) 分析持仓盈亏。

9121

himalaya

openclaw

CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).

7921

garmin-connect

openclaw

Syncs daily health and fitness data from Garmin Connect into markdown files. Provides sleep, activity, heart rate, stress, body battery, HRV, SpO2, and weight data.

7321

You might also like

flutter-development

aj-geddes

Build beautiful cross-platform mobile apps with Flutter and Dart. Covers widgets, state management with Provider/BLoC, navigation, API integration, and material design.

643969

drawio-diagrams-enhanced

jgtolentino

Create professional draw.io (diagrams.net) diagrams in XML format (.drawio files) with integrated PMP/PMBOK methodologies, extensive visual asset libraries, and industry-standard professional templates. Use this skill when users ask to create flowcharts, swimlane diagrams, cross-functional flowcharts, org charts, network diagrams, UML diagrams, BPMN, project management diagrams (WBS, Gantt, PERT, RACI), risk matrices, stakeholder maps, or any other visual diagram in draw.io format. This skill includes access to custom shape libraries for icons, clipart, and professional symbols.

591705

ui-ux-pro-max

nextlevelbuilder

"UI/UX design intelligence. 50 styles, 21 palettes, 50 font pairings, 20 charts, 8 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app, .html, .tsx, .vue, .svelte. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient."

318398

godot

bfollington

This skill should be used when working on Godot Engine projects. It provides specialized knowledge of Godot's file formats (.gd, .tscn, .tres), architecture patterns (component-based, signal-driven, resource-based), common pitfalls, validation tools, code templates, and CLI workflows. The `godot` command is available for running the game, validating scripts, importing resources, and exporting builds. Use this skill for tasks involving Godot game development, debugging scene/resource files, implementing game systems, or creating new Godot components.

339397

nano-banana-pro

garg-aayush

Generate and edit images using Google's Nano Banana Pro (Gemini 3 Pro Image) API. Use when the user asks to generate, create, edit, modify, change, alter, or update images. Also use when user references an existing image file and asks to modify it in any way (e.g., "modify this image", "change the background", "replace X with Y"). Supports both text-to-image generation and image-to-image editing with configurable resolution (1K default, 2K, or 4K for high resolution). DO NOT read the image file first - use this skill directly with the --input-image parameter.

451339

fastapi-templates

wshobson

Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.

304231

Stay ahead of the MCP ecosystem

Get weekly updates on new skills and servers.