convex-optimization-solver

Solve convex optimization problems efficiently

509 stars

Best use case

convex-optimization-solver is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Solve convex optimization problems efficiently

Teams using convex-optimization-solver 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/convex-optimization-solver/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/mathematics/skills/convex-optimization-solver/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/convex-optimization-solver/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How convex-optimization-solver Compares

Feature / Agent	convex-optimization-solver	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Solve convex optimization problems efficiently

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

# Convex Optimization Solver

## Purpose

Provides capabilities for formulating and solving convex optimization problems efficiently and reliably.

## Capabilities

- Linear programming (LP)
- Quadratic programming (QP)
- Second-order cone programming (SOCP)
- Semidefinite programming (SDP)
- Conic optimization
- Duality analysis

## Usage Guidelines

1. **Convexity Verification**: Confirm problem convexity
2. **Formulation**: Express problem in standard conic form
3. **Solver Selection**: Choose solver based on problem structure
4. **Duality**: Extract dual variables for sensitivity analysis

## Tools/Libraries

- CVXPY
- Gurobi
- MOSEK
- SCS
- ECOS

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