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 a set of principles for structuring, invoking, and pruning skills so the agent follows the same process on every run. ## Core Features & Use Cases - Invocation Design: Explains the trade-off between model-invoked skills (agent-discoverable, with context load) and user-invoked skills (human-triggered, zero context load), including router skills for managing many user-invoked skills. - Information Hierarchy: Defines how to arrange steps and reference material across SKILL.md and disclosed files using progressive disclosure and context pointers. - Failure Mode Diagnosis: Catalogs failure modes such as premature completion, duplication, sediment, sprawl, no-ops, and negation, each paired with its cure. - Use Case: When editing a skill whose agent keeps rushing through 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 reference and identify failure modes like duplication, sprawl, or premature completion.
