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llm-application-dev-prompt-optimize

llm-application-dev-prompt-optimize

github.com/sickn33Agent workflows48.7k338 installsUpdated today
Repository

About llm-application-dev-prompt-optimize

llm-application-dev-prompt-optimize is a skill for prompt optimization work. It helps clarify goals and constraints, develop actionable changes, and validate them against a task- and model-specific baseline rather than assuming universal gains.

Key features

  1. 01Clarify goals, constraints, and inputs
  2. 02Apply prompt optimization practices
  3. 03Validate optimization outcomes
  4. 04Provide actionable steps
  5. 05Consult the implementation playbook as needed

Use cases

  1. 01Improve prompts for a specific LLM task
  2. 02Create a checklist for prompt optimization
  3. 03Evaluate how prompt changes affect quality

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/sickn33/agentic-awesome-skills --skill llm-application-dev-prompt-optimize

After installing, type/llm-application-dev-prompt-optimizein Claude Code to confirm it loaded.

Bundled filesresources/implementation-playbook.md

Details

From the project README

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.

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.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Comments

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