empirical-prompt-tuning

Prompt trigger testing uses scenario-based checklists and subagent execution to empirically verify whether your skill or instruction block activates when users phrase requests in realistic ways, replacing guesswork with repeatable evaluation.

Inconsistent prompt triggers often stem from ambiguous or overfit wording. Trace analysis inspects execution-level failures and tool usage patterns, applying the smallest useful prompt change until failure patterns stop recurring across multiple test scenarios.

Validate new prompts by running scenario-based execution through a separate subagent, scoring each run with a fixed checklist, and comparing the agent's self-report against objective results to reduce bias before iterative refinement.

Prompt variant comparison applies quantitative metrics across multiple execution scenarios, tracking retries and tool usage to identify structurally weak wording, then iteratively refines until improvement plateaus and ambiguities stop recurring.

Empirical evaluation applies to skills, slash commands, task prompts, CLAUDE.md sections, and code-generation instructions whenever trigger wording is unclear, behavior is inconsistent, or a revised prompt needs validation.

Empirical prompt evaluation is unnecessary when trigger wording is already clear and behavior is consistent; it targets scenarios where prompts are ambiguous, overfit, or structurally weak and require bias-reduced subagent execution to diagnose failures.