multiAI Summary Pending
llm-application-dev-prompt-optimize
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 optimizati
231 stars
Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/llm-application-dev-prompt-optimize/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/sickn33/llm-application-dev-prompt-optimize/SKILL.md"
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/llm-application-dev-prompt-optimize/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How llm-application-dev-prompt-optimize Compares
| Feature / Agent | llm-application-dev-prompt-optimize | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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 optimizati
Which AI agents support this skill?
This skill is compatible with multi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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. Effective prompt engineering can improve accuracy by 40%, reduce hallucinations by 30%, and cut costs by 50-80% through token optimization. ## Requirements $ARGUMENTS ## Instructions - Clarify goals, constraints, and required inputs. - Apply relevant best practices and validate outcomes. - Provide actionable steps and verification. - If detailed examples are required, open `resources/implementation-playbook.md`. ## Resources - `resources/implementation-playbook.md` for detailed patterns and examples.