Total 55,831 skills, AI & Machine Learning has 9271 skills
Showing 12 of 9271 skills
Use Chanjing TTS API to synthesize speech from text, using user-provided voice
Use this skill any time the user wants to generate, create, or design images, illustrations, or visual assets. This includes: posters, banners, social media graphics, product mockups, logo concepts, thumbnails, marketing creatives, profile pictures, book covers, album art, icon designs, and any request for AI-generated imagery. Also trigger when: user says 生成图片, 做个海报, 画个插图, 设计个banner, 做个封面, 社交媒体配图, 产品效果图. If an image or visual asset needs to be created, use this skill.
ALWAYS use this skill before answering brainstorming, ideation, prompt crafting, or open-ended exploration requests. Transforms vague requests into actionable outputs via adaptive guided questioning — triages into Prompt Mode (craft/improve prompts), Explore Mode (brainstorm ideas), or Focused Mode (specific problem strategies). Trigger when user says: "brainstorm", "ช่วยคิด", "help me think", "I have an idea", "improve this prompt", "let's explore", "I want to build", "I'm thinking about", "brainstorm วิธี", "ช่วยคิดหน่อย", "อยากทำ", "ยังไม่รู้จะทำอะไร", "not sure about the approach", "help me figure out", "what should I". Also trigger for: side projects, career decisions, project planning, migration strategies, architecture decisions, cost optimization, or any request where the user hasn't decided direction yet and would benefit from structured discovery. Do NOT skip — this skill adapts depth automatically (2-7 questions) and produces BETTER results by asking targeted questions first.
Arquitecto de soluciones digitales basadas en IA. Dos modos: (1) ANALIZAR repositorios o código existente y explicar su arquitectura para cualquier audiencia, incluyendo personas sin conocimiento técnico. (2) DISEÑAR la arquitectura completa de sistemas nuevos que usan LLMs, RAG, agentes o fine-tuning. Usa este skill cuando el usuario mencione: arquitectura de IA, diseño de sistema con LLM, capas arquitectónicas, RAG architecture, tech stack para IA, vector database, diagrama de arquitectura, componentes del sistema, embedding, retrieval, pipeline de datos, MLOps, LLMOps, evaluar enfoques, RAG vs fine-tuning, diseñar solución de inteligencia artificial, explicar repositorio, explicar código, analizar proyecto, qué hace este repo, cómo funciona este sistema, explícame este proyecto, o cualquier variación de "qué componentes necesito" o "explícame cómo funciona esto". Actívalo cuando el usuario pegue código, README, estructura de archivos, o mencione un repositorio de GitHub para analizar. También cuando quiera diseñar arquitectura nueva.
Use when the user is shaping how one model request or request family should be instructed or templated, including prompt slots, input/instruct/info layering, mappings, recursive placeholder injection, prompt config, YAML or config-file-driven prompt behavior, and reusable prompt structure.
Create videos from a text prompt using HeyGen's Video Agent. Use when: (1) Creating a video from a description or idea, (2) Generating explainer, demo, or marketing videos from a prompt, (3) Making a video without specifying exact avatars, voices, or scenes, (4) Quick video prototyping or drafts, (5) One-shot prompt-to-video generation, (6) User says "make me a video" or "create a video about X".
ISO 42001 AI Management System compliance automation. Assesses organizational readiness for AIMS certification, evaluates AI system impacts, validates governance structures, and checks Annex A controls. Use for ISO 42001 readiness assessments, AI governance planning, AI impact assessments, responsible AI implementation, and AIMS certification preparation.
Instrument Python LLM apps, build golden datasets, write eval-based tests, run them, and root-cause failures — covering the full eval-driven development cycle. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM, even if they don't say "evals" explicitly. Use for making sure an AI app works correctly, catching regressions after prompt changes, debugging why an agent started behaving differently, or validating output quality before shipping.
Create, update, refactor, explain, or review Microsoft Agent Framework solutions using shared guidance plus language-specific references for .NET and Python.
Prevents premature execution on ambiguous requests. Analyzes request clarity using 5W1H decomposition, surfaces hidden assumptions, and generates structured clarifying questions before work begins. Use at the start of any non-trivial task, or when a request could be interpreted multiple ways. Triggers on "뭘 원하는건지", "요구사항 정리", "clarify", "what exactly", "scope", "requirements", "정확히 뭘", "before we start".
Agent harness performance system for Claude Code and other AI coding agents — skills, instincts, memory, hooks, commands, and security scanning
Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents.