Write and optimize prompts for LLMs and AI agents.
npx skills add https://github.com/michael-h-patrianna/animations --skill prompt-writer
Please help me install this Agent Skill. Skill: prompt-writer Source: https://github.com/michael-h-patrianna/animations/tree/main/.claude/skills/prompt-writer Command: npx skills add https://github.com/michael-h-patrianna/animations --skill prompt-writer
This Skill helps users design clear, reliable prompts for LLMs and AI agents, reducing hallucinations and improving consistency across systems.
Read references/prompting-guide.md and craft a system prompt for an AI agent that analyzes a user requirement and outputs a structured task plan.
High-intent search queries and answers about installing and using this skill.
Prompt-writer guides you through structured prompt construction using context, role, task, format, examples, and constraints. This approach minimizes hallucinations by making LLM behavior explicit and measurable, ensuring consistent outputs across different scenarios.
Design agent-specific prompts by defining the agent's role, task requirements, tool usage specifications, and verification steps. Prompt-writer includes patterns for embedding these elements and a reference guide to optimize reliability and prevent drift in agent behavior.
Use explicit output format definitions, clear constraints, and structured reasoning processes within your prompt. Prompt-writer provides a step-by-step framework to embed these requirements so LLMs generate consistent, parseable results without guessing your intent.
Yes. Prompt-writer supports reviewing and optimizing existing prompts against the comprehensive prompting guide. Load your current prompt and apply the framework to identify missing constraints, clarify task definition, or add verification steps that improve output quality.
The reference guide covers guided prompt construction techniques, including role definition, task framing, output format specification, constraint definition, example selection, and reasoning process design. Apply these patterns to chatbots, agents, instruction sets, and other LLM-based applications.
No. Prompt-writer provides structured patterns and a reference guide that make prompt design accessible. The step-by-step framework guides you through each component—context, constraints, formats—so you can build reliable prompts without prior prompt engineering knowledge.
CenredJunOptimizes prompts for LLMs to improve output accuracy and consistency.
BoraPerusicOptimize LLM prompts with RSCIT, chain-of-thought, and few-shot patterns.
infantesromeroadrianTrack prompt versions and A/B test variants using Python and Langfuse.
drgaciwImplement RAG systems integrating vector databases and semantic search for LLM applications.
