optim-agent

Optim Agent

Overview

Use this skill to optimize configurable systems against a measurable scalar objective. It helps an agent turn vague tuning requests into bounded experiments with a defined search space, budget, baseline, and evidence-backed recommendation.

When to Use This Skill

• Use when tuning hyperparameters, prompts, inference settings, simulation parameters, quantitative strategies, or RL/control policies.
• Use when the objective can be measured as a scalar score, loss, accuracy, cost, latency, reward, or risk-adjusted metric.
• Use when the user needs a small-budget optimization loop with trial history, comparisons, and stop criteria.

Do not use this skill when

• The objective is purely subjective and cannot be scored consistently.
• The user has not provided permission to run experiments or consume compute/API budget.
• The task is a one-shot implementation, debugging, or code review request with no configurable search space.

Instructions

1. Define the optimization target in one sentence: maximize or minimize one scalar metric.
2. List the tunable parameters, valid ranges, types, defaults, and any forbidden combinations.
3. Establish at least one baseline before proposing agent-guided trials.
4. Set the budget up front: number of trials, time, compute, money, or dataset subsample.
5. Run or request trials one at a time unless the user explici