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Found 320 Skills
Process and generate multimedia content using Google Gemini API for better vision capabilities. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (better image analysis than Claude models, captioning, reasoning, object detection, design extraction, OCR, visual Q&A, segmentation, handle multiple images), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image with Imagen 4, editing, composition, refinement), generate videos (text-to-video with Veo 3, 8-second clips with native audio). Use when working with audio/video files, analyzing images or screenshots (instead of default vision capabilities of Claude, only fallback to Claude's vision capabilities if needed), processing PDF documents, extracting structured data from media, creating images/videos from text prompts, or implementing multimodal AI features. Supports Gemini 3/2.5, Imagen 4, and Veo 3 models with context windows up to 2M tokens.
Chain multiple AI steps into one reliable pipeline. Use when your AI task is too complex for one prompt, you need to break AI logic into stages, combine classification then generation, do multi-step reasoning, build a compound AI system, orchestrate multiple models, or wire AI components together. Powered by DSPy multi-module pipelines.
Implements media and file management components including file upload (drag-drop, multi-file, resumable), image galleries (lightbox, carousel, masonry), video players (custom controls, captions, adaptive streaming), audio players (waveform, playlists), document viewers (PDF, Office), and optimization strategies (compression, responsive images, lazy loading, CDN). Use when handling files, displaying media, or building rich content experiences.
Assigns confidence scores to agent outputs based on multiple factors including source quality, consistency, and reasoning depth. Produces calibrated confidence estimates. Activate on 'confidence score', 'how confident', 'certainty level', 'output confidence', 'reliability score'. NOT for validation (use dag-output-validator) or hallucination detection (use dag-hallucination-detector).
Write C++ code following Sean Parent's "No Raw Loops" philosophy. Emphasizes algorithm-based thinking, composition over iteration, and treating code as mathematical reasoning. Use when refactoring or writing new C++ to maximize clarity and correctness.
Aesthetic assessment and remix partner with trained visual taste. Provides structured design critiques using a 6-dimension scoring system inspired by VisualQuality-R1 chain-of-thought reasoning.
This skill is to be used when users request in-depth analysis, thorough thinking, or detailed breakdown of a problem. It is triggered by expressions such as: 'Help me think deeply', 'Please analyze carefully', 'Help me break it down in detail', 'Please organize my thoughts', 'Think carefully', 'Gain in-depth understanding', 'Analyze in detail', or similar phrases indicating a need for systematic thinking. This skill adopts the ReAct-Plan framework: integrating chain-of-thought reasoning with explicit global planning, dynamic prediction, and reflection to overcome short-sighted behaviors.
Before starting any significant task, force explicit evaluation of available skills. For each potentially relevant skill, state YES/NO with reasoning. Only proceed to implementation after skills have been consciously evaluated and activated. Prevents the ~50% "coin flip" activation rate that occurs when skills are passively available but not deliberately considered.
Comprehensive DeepResearch methodology for conducting rigorous, traceable research projects with quality gates, structured analysis, and decision-ready deliverables. Use when (1) Conducting deep research projects requiring evidence-based analysis, (2) Managing research progress with quality gates and artifacts, (3) Producing research reports with traceable sources and structured reasoning, (4) Applying OSINT verification techniques, (5) Using structured analytic techniques (ACH, Key Assumptions Check, Red Team), (6) Expressing uncertainty and confidence in research findings, (7) Ensuring research deliverables meet intelligence tradecraft standards (ICD 203/206/208)
AI generation provenance and audit trail tracking. Records decision factors, data lineage, reasoning chains, confidence scoring, and cost tracking for AI-generated content.
Sistema para convertir logros tecnicos en narrativas que comunican senioridad e impacto. Usar cuando el usuario necesite escribir sobre sus proyectos, preparar presentaciones tecnicas, documentar decisiones de arquitectura, o comunicar complejidad a audiencias no-tecnicas. Activa con palabras como explicar proyecto, presentacion, documentar, caso de estudio, blog tecnico, conferencia. Especializado en developers senior que necesitan comunicar impacto business.
Advanced context engineering techniques for AI agents. Token-efficient plugins improving output quality through structured reasoning, reflection loops, and multi-agent patterns.