What problem does it solve? AI coding assistants often over-engineer solutions by adding unrequested abstractions, new dependencies, and speculative scaffolding. This Skill constrains code generation to the minimum change that actually works, reducing maintenance burden and code bloat. ## Core Features & Use Cases - Solution Ladder: Forces a decision hierarchy from "does this need to exist" through reuse, stdlib, native platform features, and existing dependencies before writing new code. - Intensity Levels: Switchable modes (lite, full, ultra) control how aggressively simplification is applied, with full as the default. - Root-Cause Bug Fixing: Requires tracing all callers of a function before editing, so fixes land once in the shared path instead of patching symptoms. - Use Case: When asked to add a response cache, instead of generating a custom cache class, the Skill applies @lru_cache(maxsize=1000) and notes when a custom cache would become necessary. ## Quick Start Ask the assistant to refactor or implement a coding task with ponytail active, for example: "Add caching to this API fetch function using the simplest approach."
