SkillDevelopment & Engineering
Trace a request through a codebase
Follow one request from entry point to storage or external boundary with concrete file references.
✳Claude Code
By Dave AIDave AI original
MIT · FreeView skill
Improve LLM prompts using task-specific evaluation, structured instructions, and regression checks.
--- name: llm-application-dev-prompt-optimize description: "Improve LLM prompts using task-specific evaluation, structured instructions, and regression checks." risk: safe source: community date_added: "2026-02-27" --- # 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.--- name: llm-application-dev-prompt-optimize description: "Improve LLM prompts using task-specific evaluation, structured instructions, and regression checks." risk: safe source: community date_added: "2026-02-27" --- # 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.
Imported SKILL.md format for Claude Code, Codex and Cursor. Review the complete instructions and required tools before use. Package integrity checked; individual agent behavior has not been tested.