Improve prompts for AI agents using prompt engineering standards.
npx skills add https://github.com/zmre/nix-pai --skill prompting-zmre
Please help me install this Agent Skill. Skill: prompting Source: https://github.com/zmre/nix-pai/tree/main/claude/skills/prompting Command: npx skills add https://github.com/zmre/nix-pai --skill prompting-zmre
Crafting effective prompts to get desired outputs from Claude can be iterative and challenging. This skill provides structured workflows and best practices to streamline prompt engineering, ensuring you achieve precise and high-quality results efficiently and consistently.
Use the prompting skill to create a new prompt for generating marketing slogans for a new coffee brand.
High-intent search queries and answers about installing and using this skill.
Prompt optimization uses structured techniques like clear instructions, relevant context, and iterative refinement to improve AI outputs. This skill provides workflows for testing and refining prompts systematically until you achieve desired results consistently.
Effective prompts combine Background Information, clear Instructions, Examples, and Constraints in Markdown format. Structuring prompts this way reduces token usage, enables just-in-time loading, and ensures agents understand your requirements precisely.
Prompt engineering for workflows involves designing modular, self-contained instructions that manage context efficiently and guide agents through repeatable tasks. This skill teaches techniques for designing prompts that produce reliable, consistent results across multiple runs.
Yes. Prompt optimization applies refinement techniques and testing strategies to existing prompts, helping you identify what works, eliminate inconsistencies, and boost accuracy without starting from scratch.
Inconsistent outputs often stem from unclear instructions or missing context. Use iterative prompt refinement to add specificity, examples, and constraints progressively, testing at each step until outputs meet your quality standards.
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zhangzhang-111-iAnalyze and optimize LLM prompts for clarity and token efficiency.
89jobrienOptimize LLM prompts with structured design, few-shot patterns, and chain-of-thought reasoning.
