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Found 441 Skills
Generate PhD-level expert agent prompts for Claude Code. Creates comprehensive 500-1000 line agents with detailed patterns, code examples, and best practices. Triggers on: spawn agent, create agent, generate expert, new agent, agent genesis.
Build, validate, and deploy LLM-as-Judge evaluators for automated quality assessment of LLM pipeline outputs. Use this skill whenever the user wants to: create an automated evaluator for subjective or nuanced failure modes, write a judge prompt for Pass/Fail assessment, split labeled data for judge development, measure judge alignment (TPR/TNR), estimate true success rates with bias correction, or set up CI evaluation pipelines. Also trigger when the user mentions "judge prompt", "automated eval", "LLM evaluator", "grading prompt", "alignment metrics", "true positive rate", or wants to move from manual trace review to automated evaluation. This skill covers the full lifecycle: prompt design → data splitting → iterative refinement → success rate estimation.
Design LLM-as-Judge evaluators for subjective criteria that code-based checks cannot handle. Use when a failure mode requires interpretation (tone, faithfulness, relevance, completeness). Do NOT use when the failure mode can be checked with code (regex, schema validation, execution tests). Do NOT use when you need to validate or calibrate the judge — use validate-evaluator instead.
Transform song lyrics into vivid visual scene descriptions and image generation prompts — filtering for concrete imagery and rendering each distinct scene as a numbered canvas.
Expert guidance for Anthropic Claude API development including Messages API, tool use, prompt engineering, and building production applications with Claude models.
Craft model-specific prompts optimized for the target checkpoint and identity method. Handles FLUX, SDXL, SD1.5, and Wan video models with proper syntax, quality tags, and negative prompts. Use when generating or refining prompts for ComfyUI workflows.
Optimizer that refines and professionalizes AI agent skills through real usage — saves tokens, eliminates redundancy, and tightens instructions so skills cost less to run. Learns from mistakes, reviews quality, and improves over time. Observes skill execution in the current conversation, analyzes up to four sources (conversation friction, file diffs, user feedback, static diagnostic) plus accumulated lessons, and proposes concrete improvements to the target skill's SKILL.md. Works with Claude Code and compatible SKILL.md-based agent frameworks. Use after executing any skill: `/skill-optimizer [name]` or `/skill-optimizer` to auto-detect. `--review` processes accumulated lessons.
Use this skill when the user asks to "evaluate MCP tools", "test tool selection", "improve tool descriptions", "check MCP schema quality", "eval my MCP server", or wants to measure whether Claude uses their MCP tools correctly. Tests tool selection accuracy, analyzes schema quality, and iteratively optimizes descriptions. Companion to build-mcp-server.
Turn a rough idea into a structured prompt or skill scaffold with explicit objective, inputs, workflow, outputs, and a concrete file plan. Use this whenever the user wants to design a new prompt or skill, scaffold a skill-like workflow, mentions "scaffold," "blueprint," "structure," or "plan" for a prompt, or arrives with a vague request that needs to be shaped before implementation — even if they don't explicitly ask to scaffold.
Analyze and optimize system prompts using a structured prompting guidelines framework — AI-powered analysis and rewriting. Use when a prompt needs improvement, experiment results show quality gaps, or you want a structured review of an existing system prompt. Do NOT use when production traces show failures (use analyze-trace-failures first to identify patterns). Do NOT use to build evaluators (use build-evaluator).
Expert photography prompt engineer specializing in crafting detailed, evocative prompts for AI image generation. Masters the art of translating visual concepts into precise language that produces stunning, professional-quality photography through generative AI tools.
Use when the user wants a full feature-development chain: clarify a rough feature idea into a prompt, review it with the user, then hand it to grill-with-docs, to-prd, to-issues, and tdd.