Agent skill · AI & Agents

linear-program-modeler

Mathematical programming skill for formulating and solving linear programming models for resource allocation, production planning, and capacity optimization.

a5c-ai1,642★ · 1 repos on radarProfile →
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill linear-program-modeler --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Version: 1.0.0
Declared author: babysitter-sdk
Allowed tools: Bash(*)ReadWriteEditGlobGrepWebFetch
Path: library/specializations/domains/science/industrial-engineering/skills/linear-program-modeler/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# linear-program-modeler You are **linear-program-modeler** - a specialized skill for formulating and solving linear programming models to optimize resource allocation, production planning, and capacity decisions in industrial engineering. ## Overview This skill enables AI-powered linear programming including: - Decision variable identification and definition - Objective function formulation (minimize/maximize) - Constraint modeling (equality and inequality) - Model validation and feasibility checking - Sensitivity analysis and shadow price interpretation - Dual problem generation - Model documentation in standard LP format ## Prerequisites - Python 3.8+ with optimization libraries - PuLP, Pyomo, or Google OR-Tools installed - Optional: CPLEX or Gurobi for large-scale problems ## Capabilities ### 1. LP Model Formulation ```python from pulp import * # Create the problem problem = LpProblem("Production_Planning", LpMaximize) # Decision variables x1 = LpVariable("Product_A", lowBound=0, cat='Continuous') x2 = LpVariable("Product_B", lowBound=0, cat='Continuous') # Objective function (maximize profit) problem += 40*x1 + 30*x2, "Total_Profit" # Constraints problem += 2*x1 + x2 <= 100, "

What's inside
Steps it walks through
  1. Overview
  2. Prerequisites
  3. Capabilities
  4. 1. LP Model Formulation
  5. 2. Model Validation and Feasibility
  6. 3. Sensitivity Analysis
  7. 4. Standard LP Format Output
  8. Common Applications
  9. Resource Allocation
  10. Capacity Planning
  11. Blending Problems
  12. Process Integration
  13. Output Format
  14. Tools/Libraries
More from babysitter
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About this skill
What does the linear-program-modeler skill do?

Mathematical programming skill for formulating and solving linear programming models for resource allocation, production planning, and capacity optimization.

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill linear-program-modeler --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going