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SkillsMP has collected 5,417 skills from majiayu000/claude-skill-registry. Open a skill to review its source and details.
majiayu000/claude-skill-registryShowing 40 of 5,417 collected skills.
Transformiert Anforderungen in Best-Practice Prompts nach Claude 4.x Standards (Dezember 2025). Basiert auf: - Nate B. Jones 4 Beginner Moves: Shape, Context, Silent Plan, Self-Check - Anthropic Claude 4.x Best Practices: Explizitheit, Contract-Style,…
Source text: Mixed languages
Create and enhance prompts, system instructions, and principle files. Capabilities: transform verbose prompts, add patterns/heuristics, optimize token usage, structure CLAUDE.md principles, improve agent/persona definitions, apply prompt engineering…
Build effective prompts for Claude Code skills. Creates clear, specific, actionable prompts using engineering principles, templates, and validation. Use when creating skill instructions, workflow steps, task operations, or any Claude prompt.
Prompt caching for Claude API to reduce latency by up to 85% and costs by up to 90%. Activate for cache_control, ephemeral caching, cache breakpoints, and performance optimization.
Automated prompt generation from pattern library. Input asset specifications → output production-ready Gemini prompt with validated patterns, negative constraints, and previous attempt corrections applied.
Master the Arcanean Prompt Language - advanced prompt engineering using mythological frameworks, constraint architecture, and the Centaur Principle for human-AI co-creation
Techniques and templates for creating optimal prompts following Anthropic conventions
Create context prompts for AI assistants in JSON or markdown frontmatter. Enforces mandatory context gathering (10 questions), validates schema compliance, ensures token efficiency. All content must be in English. Two types: technology-stack (project config)…
Template-based AI prompt engine with YAML templates, brand kit injection, input sanitization for security, and token-efficient context blocks.
Use when designing prompts for LLMs, optimizing model performance, building evaluation frameworks, or implementing advanced prompting techniques like chain-of-thought, few-shot learning, or structured outputs.
Expert prompt optimization for LLMs and AI systems. Use PROACTIVELY when building AI features, improving agent performance, or crafting system prompts. Masters prompt patterns and techniques.
Optimize system prompts for Claude Code agents using proven prompt engineering patterns. Use when users request prompt improvement, optimization, or refinement for agent workflows, tool instructions, or system behaviors.
Expert prompt engineering for building AI agents via Claude, GPT, and Gemini APIs. Triggers when: writing or editing system prompts, tool descriptions, agent instructions, function calling schemas, tool response design, context engineering, agentic system…
Comprehensive guide for LLM prompt engineering techniques and best practices. Prompt engineering is the art and science of crafting effective prompts to elicit desired outputs from language models.
Prompt engineering knowledge base for designing prompts, evaluating them, reviewing AI-facing assets, and improving safety, structure, and reliability.
Prompt engineering knowledge base — technique taxonomy with decision tree, prompt template patterns and formatting conventions, OWASP LLM Top 10 security checklist, eval frameworks and testing guide, context engineering, structured output contracts,…
Prompt engineering knowledge base for designing prompts, evaluating them, reviewing AI-facing assets, and improving safety, structure, and reliability.
Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.
Advanced prompt engineering techniques for optimal AI responses. Use this when crafting prompts, optimizing AI interactions, or designing system prompts for applications.
Source text: Mixed languages
LLMプロンプトの最適化・テスト支援スキル。プロンプトのパフォーマンス評価、改善提案、A/Bテスト、ベストプラクティス適用、再現性検証を行います。
Source text: Japanese
Crafting effective prompts for LLMs. Use when designing prompts, improving output quality, structuring complex instructions, or debugging poor model responses.
Interactive prompt optimization workflow for LLMs. Use when optimizing, improving, or engineering prompts for Claude, GPT, Gemini, or other language models; covers analysis, model-specific techniques, few-shot examples, XML structuring, and validation.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
Comprehensive prompt engineering with Chain-of-Thought, few-shot learning, prompt versioning, and optimization. Use when designing prompts, improving accuracy, managing prompt lifecycle.
Phase 0.2 — Enriches the raw user prompt with discovered constraints, ambiguities, likely edge cases, and suggested scope boundaries. Runs after context-gatherer, before idea-explorer questions. Generates enriched-prompt.md in the state directory.
General rules to generate prompt.
Meta-skill for improving and optimizing prompts using Anthropic's prompt engineering best practices. Provides the 4-step improvement workflow (example identification, initial draft, chain of thought refinement, example enhancement), keyword registries for…
This skill enriches vague prompts with targeted research and clarification before execution. Should be used when a prompt is determined to be vague and requires systematic research, question generation, and execution guidance.
Use when the user asks to create, refine, evaluate, or optimize an LLM prompt. Do NOT trigger for Claude Code skills (use skill-creator) or when rewriting an existing skill (use transformer). Example triggers - "write a prompt for my summarizer", "tighten…
Iterate on LLM prompts with structured evaluation and self-correction. Test prompts against ground truth, compare models, track version history. Self-correction loop sends invalid outputs back to LLM for fixing. Supports both taxonomy classification and QRA…
Guide selection of appropriate prompt level for a task. Use when choosing between simple prompts and complex workflows, applying the seven levels framework, or matching task complexity to prompt investment.
Library of 18+ ready-to-use prompt templates and executable agents
คลัง prompts แบบ minimal ที่ใช้ token น้อยที่สุดแต่ได้ผลลัพธ์ดี พร้อม templates และ best practices
Source text: Thai
Activates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.
Optimize and manage AILANG teaching prompts for maximum conciseness and accuracy. Use when user asks to create/update prompts, optimize prompt length, or verify prompt accuracy.
Optimize CLAUDE.md files and Skills for Claude Code CLI. Use when reviewing, creating, or improving system prompts, CLAUDE.md configurations, or Skill files. Transforms negative instructions into positive patterns following Anthropic's official best practices.
Analyze and improve existing prompts for better performance
A/B test CLAUDE.md instruction changes against eval benchmarks. Capture baselines, test variants, compare results.
A/B test CLAUDE.md instruction changes against eval benchmarks. Capture baselines, test variants, compare results.
Use when a draft prompt, instruction set, or agent skill description needs refinement, clarity, or improved performance.