complexity-class-oracle

Classify problems into complexity classes with supporting evidence and proof strategies

509 stars

Best use case

complexity-class-oracle is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Classify problems into complexity classes with supporting evidence and proof strategies

Teams using complexity-class-oracle should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/complexity-class-oracle/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/computer-science/skills/complexity-class-oracle/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/complexity-class-oracle/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How complexity-class-oracle Compares

Feature / Agentcomplexity-class-oracleStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Classify problems into complexity classes with supporting evidence and proof strategies

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Complexity Class Oracle

## Purpose

Provides expert guidance on classifying computational problems into complexity classes and understanding class relationships.

## Capabilities

- Determine membership in P, NP, co-NP, PSPACE, EXPTIME
- Identify complete problems for each class
- Query known complexity results database
- Suggest proof strategies for classification
- Generate complexity landscape diagrams
- Explain class inclusions and separations

## Usage Guidelines

1. **Problem Characterization**: Formalize the computational problem
2. **Class Investigation**: Check membership in relevant classes
3. **Evidence Collection**: Gather evidence for classification
4. **Strategy Selection**: Choose proof strategy for membership
5. **Documentation**: Generate classification report

## Tools/Libraries

- Complexity Zoo database
- Diagram generation
- LaTeX documentation

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