Magnus HedemarkandGitHub
f53bddcd7b
* feat(constrained-optimization): add formulation and audit methodology * docs(constrained-optimization): register skill and align trigger metadata * docs(constrained-optimization): route templates and define completion * docs(constrained-optimization): cite solver evidence and applicability
Constrained optimization
Make optimization decisions that remain valid when constraints, tradeoffs, and solver limits matter.
Why Install This Skill
Optimization results are easy to misread: a lower score may violate a hard limit, a timeout may be mistaken for infeasibility, and an average from one random run may not survive repetition. This skill gives an agent a disciplined way to state the problem before choosing a method.
It produces reviewable formulation and solution-audit records. The workflow separates feasible candidates from infeasible ones, preserves exact-solver bounds and gaps, and makes multiobjective and stochastic tradeoffs explicit.
What You Get
| Directory | Purpose |
|---|---|
SKILL.md |
Decision workflow, boundaries, and routing |
references/ |
Formulation, solver evidence, Pareto, robustness guidance, and primary-source index |
templates/ |
Formulation and solution-audit records |
evals/ |
Quality cases for common optimization failures |
Quick Start
Start with SKILL.md, then fill templates/formulation-record.md before selecting a solver. Use templates/solution-audit.md to independently verify the returned candidate.
Triggers
- Formulating a constrained optimization problem
- Comparing exact methods, heuristics, or stochastic search
- Reviewing feasibility, optimality gaps, or timeout claims
- Choosing among Pareto tradeoffs or objective priorities
Requirements
No solver, API key, or runtime is required. Named solver operation and statistical modeling remain with their respective skills.