What problem does it solve?
Prompts written for humans often contain filler, repetition, and vague wording that waste tokens and introduce ambiguity when consumed by LLMs. This Skill compresses prompts into minimal, unambiguous instructions without losing required constraints or output quality.
Core Features & Use Cases
- Token Reduction: Removes pleasantries, narrative framing, and filler words while keeping task-critical information.
- Ambiguity Elimination: Resolves undefined nouns, unclear pronouns, and vague qualifiers like "appropriate" or "some" into measurable criteria.
- LLM-Optimized Formatting: Converts prose into imperative statements, atomic bullets, and explicit output format requirements.
- Use Case: Before sending a long instruction block to an agentic workflow, run it through this Skill to cut token usage and make success criteria testable.
Quick Start
Rewrite this prompt to use fewer tokens while keeping all constraints and making the output format explicit.