What problem does it solve? Writing skills for AI agents often produces bloated, duplicated, or unreliable instructions that cause inconsistent agent behavior. This Skill supplies a shared vocabulary and decision framework for structuring, splitting, and pruning skills so agents behave predictably on every run. ## Core Features & Use Cases - Invocation Design: Guidance on choosing between model-invoked and user-invoked skills, trading context load against cognitive load. - Information Hierarchy: A three-rung ladder (steps, in-file reference, disclosed reference) with progressive disclosure rules for keeping SKILL.md legible. - Failure Diagnosis: Named failure modes — premature completion, duplication, sediment, sprawl, and no-ops — with concrete fixes for each. - Use Case: When editing a skill whose agent keeps skipping steps, consult the failure modes section to sharpen completion criteria or split the sequence to hide post-completion steps. ## Quick Start Ask the agent to review your SKILL.md using the writing-great-skills principles and identify no-ops, duplication, and sprawl.