Llm Application Dev Prompt Optimize

Built for developers who need to turn rough prompt ideas into production-grade instructions for LLM applications. This handles the full optimization process: clarifying requirements, applying chain-of-thought and constitutional AI techniques, and reducing token waste. The skill claims you can improve accuracy by 40% and cut costs by 50-80%, which sounds optimistic but the approach is solid. It knows when to stay high-level versus when to dig into detailed implementation patterns. Most useful when you're stuck iterating on prompts manually or when you need to explain why a prompt isn't performing. Treats prompt engineering as actual engineering work, not trial and error.

skills.sh installs: 357
GitHub stars: 39.4K
last updated: Jun 3, 2026

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Install

$ npx -y skills add sickn33/antigravity-awesome-skills --skill llm-application-dev-prompt-optimize --agent claude-code

Installs into .claude/skills of the current project.

Files

Prompt Optimization

You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimization.

Use this skill when

Working on prompt optimization tasks or workflows
Needing guidance, best practices, or checklists for prompt optimization

Do not use this skill when

The task is unrelated to prompt optimization
You need a different domain or tool outside this scope

Context

Transform basic instructions into production-ready prompts. Prompt changes can improve or worsen quality, latency and cost. Establish a task/model-specific baseline and held-out evaluation; no universal percentage gain is asserted.