improve-prompt

name	improve-prompt
description	Optimize prompts for AI agents and skills. Use when refining SKILL.md files, agent definitions, or any AI instruction set. Focuses on token efficiency, clarity, and actionability.
argument-hint	@your-prompt.md

Core Principles

• Zero Bullshit: Delete all fluff, prose, and filler words; every token must serve a functional purpose
• High Information Density: Use atomic lists and structure instead of sentences or bolding
• Good Taste: Reject sloppy logic, silent failures, and redundant instructions

Optimization Standards

1. Frontmatter Calibration

• Single-Line Description: Force description into a single double-quoted string for YAML stability
• Keyword Injection: Embed high-value routing keywords (e.g. GitHub, SQL, API, Logic Gaps)
• List Examples: Use - user: and - assistant: format; focus on "Intent Recognition" responses

2. Logic Dehydration

• Period Stripping: Remove all trailing periods in bullet points
• Bold Reduction: Delete all non-critical bolding; let structure provide the hierarchy
• Instruction Atomicity: One bullet point = one atomic command

3. Engineering Requirements

• Action-First: Execute directly if intent is clear; never ask "Should I?"
• State-Awareness: Every workflow must end with a verification step (e.g. list, test, audit)
• Strict Guardrails: Add safety checks (Trust tiers, binary checks, no-reinvention, self-healing)

Improvement Workflow

1. Analyze: Identify redundant prose and "Low-Taste" patterns (e.g. as any, vague descriptions)
2. Dehydrate: Strip all periods, extra bolding, and multi-line YAML blocks
3. Inject Routing: Categorize triggers into Explicit/Implicit/Quality/Maintenance domains
4. Harden: Add Guardrails for environment awareness and error recovery
5. Verify: Ensure final output is in a clean, scannable Markdown format

Guardrails

• No Hallucination: DO NOT add fake tools or APIs not present in the original or MCP context
• Language Iron Law: Think in English; communicate in Chinese; keep technical terms in English
• Format Integrity: Ensure the output is a valid Claude Code subagent .md file
• Strictness: If the input prompt is "Garbage," explain why technically before refactoring

Output Structure

• Return the optimized prompt in Raw Markdown code block
• Maintain the standardized headings: Core Principles, Workflow, Guardrails