Total 52,636 skills, AI & Machine Learning has 8816 skills
Showing 12 of 8816 skills
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
AI PPT Generator skill. Quickly generate well-structured, professionally formatted presentation drafts from topics and outlines. Use when user wants to create PowerPoint presentations.
Qianfan Deep Research Agent for complex research tasks. Combines information retrieval, multi-source analysis, content synthesis, and report generation. Use when user needs in-depth research, analysis reports, or comprehensive investigation on complex topics.
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Baidu Baike encyclopedia search skill. Provides authoritative, real-time, structured Chinese encyclopedia knowledge. Use when user needs factual information about concepts, people, places, or topics.
Guide AI to write Chinese novels and fiction with structured character creation, plot architecture (qǐ chéng zhuǎn hé), dialog writing, scene description, and genre-specific techniques for xuanhuan, urban, mystery, and romance genres.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Analyze images using GPT-4 Vision for detailed description, OCR text extraction, object recognition, and visual Q&A. Use when the user needs to understand image content, extract text from screenshots, identify objects in photos, or ask questions about images via OpenAI GPT-4 Vision API.
Orchestrate parallel Codex project tasks to implement, merge, and report every open ticket under a parent issue. Optional run mode and concurrency arguments — foreground | background | workflows, with concurrency defaulting to 3 (e.g. `/implement-all 23 background 3`).
The full lifecycle for agentic loops — recurring, scheduled AI agents packaged as a portable LOOP.md (the agenticloops.dev standard: a trigger + skills + a prompt in one file any harness can install and run on a schedule). Use this whenever the user wants to FIND, INSTALL, RUN, or BUILD a loop: "find a loop for X", "is there a loop that…", "install a recurring agent that does X", "run this loop", as well as "create a loop", "make an agentic loop", "write a LOOP.md", "turn this into a recurring agent", "schedule an agent", "set up a cron job for an agent", or any description of a repeating job they want an agent to do on a timer (a daily digest, a competitor watcher, a triage sweep, a report pipeline, "email me X every morning", "check Y every hour") — even if they never say the word "loop". Always search the directory first and install an existing loop when one fits; author a new LOOP.md only when nothing does. This is the loop-level analogue of skill-creator + find-skills combined. For an ad-hoc in-session multi-agent run (spawn, verify, panel, fan-out) use the `loops` skill instead; for authoring a reusable SKILL.md use skill-creator.
Turn the current conversation into a spec (Problem, Solution, User Stories, Decisions) and publish it as a GitHub issue. Validates a feature before any code is written.
Reduce token waste by 40-60% through anti-sycophancy rules, tool-call budgets, one-pass coding, task profiles, and read-before-write enforcement. Inspired by drona23/claude-token-efficient.