war-room

Solid

Convenes a multi-LLM expert panel to pressure-test hard-to-reverse decisions. Use when reversibility score is low and adversarial review is warranted.

AI & Automation 309 stars 27 forks Updated today MIT

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Quality Score: 96/100

Stars 20%
83
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100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

## Overview The War Room convenes multiple AI experts to analyze problems from diverse perspectives, challenge assumptions through adversarial review, and synthesize optimal approaches under the guidance of a Supreme Commander. ### Philosophy > "The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle." > - Marvin Minsky, Society of Mind ## Reversibility-Based Routing Before deliberation, assess the **Reversibility Score (RS)** to determine appropriate resource allocation: ``` RS = (Reversal Cost + Time Lock-In + Blast Radius + Information Loss + Reputation Impact) / 25 ``` | RS Range | Type | Mode | Resources | |----------|------|------|-----------| | 0.04 - 0.40 | **Type 2** | Express | 1 expert, < 2 min | | 0.41 - 0.60 | **Type 1B** | Lightweight | 3 experts, 5-10 min | | 0.61 - 0.80 | **Type 1A** | Full Council | 7 experts, 15-30 min | | 0.81 - 1.00 | **Type 1A+** | Delphi | 7 experts, 30-60 min | **Quick Heuristics:** - Can be A/B tested? → Type 2 - Requires data migration? → Type 1 - Public commitment required? → Type 1A+ See `modules/reversibility-assessment.md` for full scoring guide. ## When To Use - Architectural decisions with major trade-offs - Multi-stakeholder problems requiring diverse perspectives - High-stakes choices with significant consequences (RS > 0.60) - Novel problems without clear precedent - When brainstorming produces multiple strong competing approaches ## When...

Details

Author
athola
Repository
athola/claude-night-market
Created
6 months ago
Last Updated
today
Language
Python
License
MIT

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