Total 56,145 skills, AI & Machine Learning has 9349 skills
Showing 12 of 9349 skills
Comprehensive guide to AI SDK v6 for agent development, tool definitions, multi-step agentic workflows, and result extraction patterns
Prompt engineering and optimization for AI/LLMs. Capabilities: transform unclear prompts, reduce token usage, improve structure, add constraints, optimize for specific models, backward-compatible rewrites. Actions: improve, enhance, optimize, refactor, compress prompts. Keywords: prompt engineering, prompt optimization, token efficiency, LLM prompt, AI prompt, clarity, structure, system prompt, user prompt, few-shot, chain-of-thought, instruction tuning, prompt compression, token reduction, prompt rewrite, semantic preservation. Use when: improving unclear prompts, reducing token consumption, optimizing LLM outputs, restructuring verbose requests, creating system prompts, enhancing prompt clarity.
Comprehensive context management strategies for cost optimization and infinite-length conversations. Covers server-side clearing (tool results, thinking blocks), client-side SDK compaction (automatic summarization), and memory tool integration. Use when managing long conversations, optimizing token costs, preventing context overflow, or enabling continuous agentic workflows.
Write, audit, and improve agent context files (AGENTS.md, CLAUDE.md) for AI coding agents. Use when creating or improving agent context for a codebase.
Generate images with Alibaba Qwen-Image-2.0-Pro via inference.sh CLI. Professional text rendering, fine-grained realism, enhanced semantic adherence. Ideal for posters, banners, and text-heavy designs. Triggers: qwen image pro, qwen-image-pro, qwen 2 pro, alibaba image pro, dashscope pro, professional text rendering
Create AiderDesk Agent Skills by writing SKILL.md files, defining frontmatter metadata, structuring references, and organizing skill directories. Use when building a new skill, creating a SKILL.md, planning skill architecture, or writing skill content.
Autonomous skill creation agent that analyzes requests, automatically selects the best creation method (documentation scraping via Skill_Seekers, manual TDD construction, or hybrid), ensures quality compliance with Anthropic best practices, and delivers production-ready skills without requiring user decision-making or navigation
Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.
Process textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence, and file input handling.
Create hierarchical project plans optimized for solo agentic development. Use when planning projects, phases, or tasks that Claude will execute. Produces Claude-executable plans with verification criteria, not enterprise documentation. Handles briefs, roadmaps, phase plans, and context handoffs.
[Tooling & Meta] Manage learned patterns - list, view, archive, boost or penalize confidence. Use when you want to see what patterns Claude has learned, review pattern effectiveness, or manage the pattern library.
This skill should be used when the user wants to "create a skill", "add a skill to plugin", "write a new skill", "improve skill description", "organize skill content", or needs guidance on skill structure, progressive disclosure, or skill development best practices for Claude Code plugins.