Total 50,678 skills, AI & Machine Learning has 8492 skills
Showing 12 of 8492 skills
Deepgram API reference for speech-to-text, text-to-speech, voice agents, audio intelligence, and account management. Use whenever building with Deepgram APIs — REST or WebSocket. Covers authentication, all endpoints, query parameters, request/response schemas, and WebSocket message formats. Reference files are organized by domain: listen (STT), speak (TTS), agent (voice agents), read (text/audio intelligence), models, projects, auth, and self-hosted.
Use when syncing skills, MCPs, or AGENTS.md sections across coding agents with agent-install.
Use when the user asks to call a friend or get a CLI-backed second opinion from Claude, Gemini, or Codex.
English alias for /aprende. Runs the same five-pass workflow to surface reusable learnings from the current conversation across memory, lesson, skill, and project-doc categories — with confirmation before any write. Alias en inglés para /aprende.
When the user wants to build or improve a sales bot's ability to automatically test message variations to optimize conversion. Also use when the user mentions "message testing," "A/B testing bots," "optimizing bot messages," "testing variations," or "message optimization."
Uses Agent SDK to deploy 3 parallel agents for client onboarding -- workflow auditor, tech stack mapper, and strategy drafter. Real consulting workflow that produces a complete client assessment.
Validar prompts dirigidos a agentes de IA (Claude Code, Cursor, Copilot, etc.) contra reglas de redacción efectiva. Calcular un porcentaje de efectividad del prompt y devolver sugerencias de mejora concretas, más una propuesta de prompt reescrito. Cubre verbos no imperativos, lenguaje conversacional, acciones vagas, términos subjetivos, alcance difuso, prohibiciones implícitas, intenciones múltiples y nombres genéricos. Las reglas de detalle técnico (alcance, nombres exactos) se aplican solo a prompts de implementación; en prompts funcionales (user stories, descripciones de comportamiento) se marcan N/A. Usar siempre que el usuario pida validar, revisar, auditar, mejorar, corregir o "pulir" un prompt antes de enviarlo a un agente, o cuando pegue un prompt y pida feedback sobre cómo está redactado.
Index directory for automatically learned skills from execution feedback
Cram Engine - An AI tutor well-versed in learning science. Triggered when users mention terms like final exam cramming, final review, exam sprint, last-minute exam preparation, quick exam prep, intensive last-minute review, or use the /cram command. Based on six learning science principles including Cognitive Load Theory, Elaborative Processing, Generation Effect, and Retrieval Practice, it converts key points of university courses into efficient interactive learning sessions through a four-stage pipeline: deconstructing knowledge point tree → teaching each point individually → testing with real exam question types → diagnosing and filling knowledge gaps. Suitable for all qualitative knowledge-intensive university liberal arts courses.
BEVFusion for multi-sensor 3D object detection. Fuses LiDAR point clouds and camera images in bird's-eye-view (BEV) space, used in autonomous driving for robust 3D perception. Use when training, evaluating, or running inference for a TAO BEVFusion model. Trigger phrases include "train BEVFusion", "LiDAR + camera fusion", "BEV 3D detection", "multi-sensor 3D perception".
Extract false-positive and false-negative gaps from VLM binary-classification-question (BCQ, yes/no) predictions. Use after running VLM evaluation when you have a predictions JSON and need to identify failure cases for DEFT root cause analysis on a binary-classification VLM workflow.
Grounding DINO for open-set object detection. Combines DINO-style detection with a BERT text encoder for language-guided detection — detects objects described by text prompts without a fixed class vocabulary. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Grounding DINO model. Trigger phrases include "train Grounding DINO", "open-vocabulary detection", "text-prompted detector", "language-guided object detection".