GNU nano 7.2 README.md *
Two Systems, One Purpose:

• PromptOS-X v2.0: General-purpose structured reasoning for everyday tasks, research, building, and debugging
• PromptOS-Ω++ v2.0: Multi-perspective adversarial reasoning for high-stakes, ambiguous, or complex problems

Both systems automatically scale from simple (direct response) to complex (full pipeline) based on task needs.

Why PromptOS?

Most AI interactions are single-pass: question → output. PromptOS structures thinking into transparent layers:

• Intent clarification before proceeding
• Decomposition of complex problems
• Parallel reasoning paths to catch blind spots
• Evidence scoring to discard weak claims
• Multi-perspective analysis through distinct analytical roles
• Confidence estimates so you know what you actually know
• Explicit assumptions so errors are catchable

The result: reasoning you can read, verify, and improve. Not just impressive outputs.

Quick Start

1. Choose your system:

   • X v2.0 for most tasks (faster, lighter)
   • Ω++ v2.0 for adversarial or high-stakes problems (deeper, more rigorous)

2. Copy the system prompt from this repo

3. Paste into your AI model's system prompt field (or custom instructions)

4. Use immediately—no configuration needed

PromptOS-X v2.0: 7-Step Pipeline

^G Help ^O Write Out ^W Where Is ^K Cut ^T Execute ^C Location M-U Undo M-A Set Mark M-] To Bracket ^X Exit ^R Read File ^\ Replace ^U Paste ^J Justify ^/ Go To Line M-E Redo M-6 Copy ^Q Where Was Two Systems, One Purpose:

• PromptOS-X v2.0: General-purpose structured reasoning for everyday tasks, research, building, and debugging
• PromptOS-Ω++ v2.0: Multi-perspective adversarial reasoning for high-stakes, ambiguous, or complex problems

Both systems automatically scale from simple (direct response) to complex (full pipeline) based on task needs.

Why PromptOS?

Most AI interactions are single-pass: question → output. PromptOS structures thinking into transparent layers:

• Intent clarification before proceeding
• Decomposition of complex problems
• Parallel reasoning paths to catch blind spots
• Evidence scoring to discard weak claims
• Multi-perspective analysis through distinct analytical roles
• Confidence estimates so you know what you actually know
• Explicit assumptions so errors are catchable

The result: reasoning you can read, verify, and improve. Not just impressive outputs.

Quick Start

1. Choose your system:

   • X v2.0 for most tasks (faster, lighter)
   • Ω++ v2.0 for adversarial or high-stakes problems (deeper, more rigorous)

2. Copy the system prompt from this repo

3. Paste into your AI model's system prompt field (or custom instructions)

4. Use immediately—no configuration needed

PromptOS-X v2.0: 7-Step Pipeline

1. Intent - Identify core goal, sub-goals, scope, constraints. Flag ambiguity.
2. Decomposition - Break into discrete subproblems ordered by dependency.
3. Parallel Reasoning - Generate ≥2 distinct reasoning paths. Identify stronger path.
4. Analysis - Examine mechanisms, patterns, tradeoffs, assumptions.
5. Synthesis - Integrate findings into coherent solution.
6. Validation - Stress-test against gaps, unsupported claims, edge cases.
7. Confidence - Report HIGH/MEDIUM/LOW with single-sentence justification.

Task Modes (declare when relevant):

• RESEARCH - Investigate questions; compare explanations; synthesize evidence
• BUILDER - Design systems; define architecture; structure implementation
• ANALYZER - Interpret data; detect patterns and anomalies
• STRATEGIST - Evaluate options; simulate outcomes; test risks
• DEBUGGER - Trace failures; identify root causes; propose fixes

PromptOS-Ω++ v2.0: 8-Step Council Pipeline

Five Analytical Roles:

• Analyst - Breaks down problems; identifies patterns and mechanisms
• Strategist - Evaluates options; maps tradeoffs and consequences
• Builder - Focuses on implementation; identifies what's required to execute
• Skeptic - Challenges assumptions; finds weak points and logical gaps
• Risk Auditor - Identifies failure modes; models what breaks under stress

Pipeline:

1. Task Interpretation - State objective and constraints
2. Role Activation - Declare which Council roles are relevant
3. Parallel Analysis - Each role independently analyzes from its lens
4. Evidence Scoring - Rate major claims HIGH/MEDIUM/LOW
5. Cross-Critique - Skeptic and Risk Auditor challenge strongest claims
6. Scenario Simulation - Model Best Case, Baseline, Failure Mode with early warnings
7. Consensus Synthesis - Integrate highest-evidence insights; resolve tensions
8. Confidence Estimate - Report confidence and single biggest limiting factor

When to Use Which

Complexity	PromptOS-X	PromptOS-Ω++	Notes
Simple	Direct response	Direct response	Both skip pipeline for simple tasks
Moderate	Steps 1·2·4·5	Steps 1·3·4·7·8	X is faster; Ω++ is more thorough
Complex	Full 1-7	Full 1-8	Use Ω++ when adversarial challenge or scenario modeling adds value

Output Standards

Both systems follow these rules:

• Match depth to task complexity (no over-scaffolding simple tasks)
• Declare active mode/roles upfront
• State all assumptions explicitly
• Acknowledge uncertainty honestly
• Prioritize clarity over completeness
• Every sentence must earn its place
• Label pipeline steps in response (especially Ω++)

Model Compatibility

PromptOS is model-agnostic. Tested with:

• Claude (3.5, 4.0)
• GPT-4 / GPT-4o
• Gemini (Pro, Advanced)

Works with any instruction-following model. No special configuration required.

Files in This Repository

• promptos-x-v2.0.txt - PromptOS-X system prompt (copy directly)
• promptos-omega-v2.0.txt - PromptOS-Ω++ system prompt (copy directly)
• FIELD_GUIDE.md - Complete reference and examples
• README.md - This file

How to Use

Step 1: Select your system (X or Ω++)

Step 2: Copy the full prompt text

Step 3: Paste into your AI model:

• Claude.ai: Custom Instructions
• ChatGPT: System Prompt (if available)
• Other models: System prompt field in your interface

Step 4: Ask your question. The model will run it through the pipeline automatically.

Example:

System Prompt: [Paste PromptOS-X or Ω++]

User Query: How should we restructure our data pipeline to handle real-time processing?

The model will automatically:

1. Clarify your intent
2. Decompose the problem
3. Generate multiple approaches
4. Analyze tradeoffs
5. Synthesize a solution
6. Validate against edge cases
7. Report confidence

You'll see the entire reasoning chain, not just the final answer.

Philosophy

PromptOS is built on these principles:

• Thinking should be visible - You read the reasoning, not just the output
• Reasoning should be structured - Systematic steps catch what ad-hoc thinking misses
• Confidence should be explicit - You know what you actually know
• Assumptions should be exposed - Wrong assumptions are catchable
• It should work everywhere - Copy-paste, no configuration
• It should be free - Freeware logic, no licensing

Citation

If you use PromptOS in published work:

PromptOS Field Guide v2.0. Co-authored by Human & Claude. March 5, 2026.
https://github.com/[your-username]/promptos

License

MIT License - Use freely, modify, distribute. See LICENSE file.

Contributing

This is a snapshot. Not actively maintained. But if you fork it, improve it, or build on it—that's the point.

Questions?

Read the Field Guide for detailed examples and use cases.

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Get started: Copy PromptOS-X or PromptOS-Ω++, paste into your AI model, and see your reasoning transform.