Claude Code Prompt Improver

Claude Code Prompt Improver

Intelligent prompt optimization for Claude Code. It injects the right context at the right moment - at prompt submit, tool use, and subagent start - so Claude has what it needs before it acts. The goal is a better first output, so you spend fewer turns correcting it.

Prompt improvement here means improving the whole path from your prompt to Claude's output, not just rewriting the words you typed. Clarifying a vague prompt is one way to do that. Supplying a constraint you would otherwise have had to add by hand after a bad first attempt is another. Both land the output sooner.

What It Does

A small set of targeted nudges fire only when they apply, each one supplying context that would otherwise cost a correction round-trip:

Two nudges evaluate every prompt. improve checks clarity:
- For clear prompts: proceeds immediately (zero skill overhead)
- For vague prompts: invokes the prompt-improver skill to create a research plan, gather context, and ask 1-6 grounded questions, then proceeds with the clarification

plan-mode runs alongside it, judging whether the task is complex enough to plan before acting - it self-cancels on anything trivial.

The other seven fire only when they apply. The keyword-gated ones (workflow, approach-assessment, output-readability, ask-user-question, background-exec) lead with a condition ("If this is X... if not, ignore"), so a false fire is dismissed cheaply; the exact-gated ones (plan on plan-mode entry, subagent-routing on a research agent) only fire when the condition is already certain.

Result: Better outcomes on the first try, without back-and-forth.

v0.4.0 Update: Skill-based architecture with hook-level evaluation achieves 31% token reduction. Clear prompts have zero skill overhead, vague prompts get…