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Found 46 Skills
Team composition knowledge for Claude Code Agent Teams - when to suggest teams, optimal sizing, spawn prompt patterns
Create, improve, or optimize prompts using best practices
Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
Engineer system prompts for LiveKit voice agents with multilingual support. Use when creating or optimizing AI agent conversation flows.
Use this skill when crafting, iterating, or optimizing prompts for LLMs including zero-shot, few-shot, chain-of-thought, role prompting, structured output, and prompt chaining. Not for fine-tuning or training models. Not for evaluating model quality across benchmarks.
This skill should be used when the user asks to "ask questions interactively", "use the question tool", "present choices to the user", "avoid yes/no prompts", "use interactive confirmations", or needs guidance on asking structured questions with selectable options instead of free-text prompts.
Page-level slide prompting skill. Converts DESIGN.md and slide_plan.json into detailed slide-generation prompts in JSON while preserving theme, body-slide consistency, and layout discipline.
Design, test, and optimize prompts for LLM interactions. Cover prompt patterns (few-shot, chain-of-thought, ReAct), system prompt design, output formatting, prompt evaluation, and prompt optimization techniques. Triggers on "write prompt", "optimize prompt", "design system prompt", "few-shot examples", "chain of thought", "prompt evaluation", "LLM output formatting", "prompt testing", or "prompt patterns".
Writes, rewrites, diagnoses, and improves any LLM prompt with minimal, high-signal edits. Use when the user wants to create a new prompt from scratch, review or fix a prompt that produces poor output, simplify or tighten instructions, restructure a long prompt, port a prompt between models, or expand an existing prompt. Covers system prompts, agent instructions, CLAUDE.md rules, SKILL.md prompt bodies, chat templates, structured-output prompts, RAG context templates, and prompt strings embedded in code. Also use when editing any file whose primary content is LLM instructions.
Provide concrete examples—existing code patterns, style samples, input/output pairs—to guide AI toward your project's conventions