What problem does it solve? Writing an effective skill is hard to get right on the first try, and there is no built-in way to know whether a skill actually improves Claude's output or triggers when it should. This Skill provides a structured draft-test-review-improve loop with quantitative benchmarking so skill authors can iterate based on evidence instead of guesswork. ## Core Features & Use Cases - Guided Skill Authoring: Interviews the user about intent, trigger contexts, and output formats, then drafts a SKILL.md following progressive disclosure and writing-style best practices. - Evaluation Harness: Runs test prompts with and without the skill in parallel subagents, grades outputs against assertions, and aggregates pass rates, timing, and token usage into benchmark reports. - Description Optimization: Generates realistic trigger/no-trigger eval queries and runs an automated optimization loop to improve the skill description's triggering accuracy, with train/test splits to avoid overfitting. - Use Case: A user wants a skill that formats weekly sales spreadsheets. This Skill helps draft it, runs three realistic test prompts with baseline comparisons, presents results in an HTML review viewer, and iterates until the outputs satisfy the user. ## Quick Start Help me create a new skill that converts meeting notes into structured action items, then test it with a few realistic prompts.
