Total 56,068 skills, AI & Machine Learning has 9341 skills
Showing 12 of 9341 skills
Guide for creating custom Claude Code slash commands. Use when user wants to create a new command (or update an existing command) that provides a reusable prompt snippet, workflow, or automation. Triggers on requests to create /commands, slash commands, custom commands, or when user wants to define frequently-used prompts as reusable commands.
Specialized feature development agents. Use for deep codebase exploration and architecture design during feature development.
Invokes Google Gemini models for structured outputs, multi-modal tasks, and Google-specific features. Use when users request Gemini, structured JSON output, Google API integration, or cost-effective parallel processing.
Génère des images heroic fantasy pour BFRPG via fal.ai FLUX.1. Portraits de personnages/PNJ, scènes d'aventure, monstres, objets magiques et lieux. Utilise des prompts optimisés pour le style fantasy médiéval.
AI Native Camp Day 4 Wrap & Analyze. session-wrap 스킬을 직접 만들고, history-insight와 session-analyzer로 세션을 분석한다. "4일차", "Day 4", "wrap", "세션 분석", "session wrap", "세션 래핑" 요청에 사용.
Explain maps, variants, and curriculum ordering used by a training command or recipe. Use when asked to audit a recipe configuration.
AI agent-focused RSS feed discovery tool with JSON output. Use when Claude needs to discover RSS/Atom feeds from websites for monitoring, aggregation, or content syndication purposes. Triggered by: "find RSS feed", "discover RSS", "find Atom feed", "get RSS URLs", "find feeds from [URL]", or when working with content aggregation, feed readers, or RSS monitoring workflows.
Scaffold a complete knowledge system. Detects platform, conducts conversation, derives configuration, generates everything. Validates against 15 kernel primitives. Triggers on "/setup", "/setup --advanced", "set up my knowledge system", "create my vault".
Audit and manage the full project context landscape: CLAUDE.md memory hierarchy, project documentation, markdown footprint, and content overlap. Detects project type, scores quality, flags stale docs, and reports total context cost. Trigger with 'audit context', 'audit memory', 'update CLAUDE.md', 'restructure memory', 'session capture', 'check project docs', 'markdown footprint', or 'what docs does this project need'.
Agent skill for migration-plan - invoke with $agent-migration-plan
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.
Score assistant responses for guidance & actionability on a strict 1-5 scale, then return strict JSON only with dimension, score, rationale, and improvement suggestions. Use when the user asks to evaluate how actionable, helpful, or step-by-step a response is.