Loading...
Loading...
Found 11,816 Skills
Overview The Instagram Agent allows users to extract data from Instagram, including posts, profiles, hashtags and comments, to bypass limitations of manual research. By using the Instagram Agent, bu
Use when executing multi-task plans where each task can be implemented independently by a subagent. Triggers when a plan has 3+ independent tasks, when speed of execution is important, when tasks have clear acceptance criteria suitable for delegation, or when two-stage review gates (spec compliance and code quality) are needed for iterative fix cycles.
Vercel agent-browser — Rust CLI for AI-driven browser automation via CDP. Use when: "agent-browser", "browse website", "automate browser", "scrape with browser", "fill form", "click button", "take screenshot", "browser automation", "headless chrome", "web interaction", "accessibility snapshot", "browser refs". Deterministic ref-based selectors, JSON output, daemon architecture. Replaces Playwright/Puppeteer for agent workflows.
Use when you need to install the embedded robot agents into either .cursor/agents or .claude/agents, selecting the destination interactively and copying the embedded agent definitions from project assets. Part of the skills-for-java project
Master problem solver for systematic problem-solving methodologies. Use when the user asks to talk to Dr. Quinn or requests the Master Problem Solver.
Design, create, and configure orq.ai Agents with tools, instructions, knowledge bases, and memory stores. Use when building new agents, attaching KBs or memory, writing system instructions, selecting models, or setting up RAG pipelines. Do NOT use for debugging existing agents (use analyze-trace-failures) or comparing agents across frameworks (use compare-agents).
Create and manage agent graphs — directed graphs of configs connected by edges with handoff logic. Use when building multi-agent workflows where configs route to each other.
Use when the user is doing AI/ML work in a scientific domain — biology, chemistry, physics, astronomy, climate, genomics, materials science, medicine, ecology, energy, conservation, engineering, mathematics, scientific reasoning, drug discovery, protein design, weather modeling, theorem proving, single-cell, PDE solving, or anything similar. Hugging Science (huggingscience.co) is a curated catalog of scientific datasets, models, blog posts, and interactive Spaces; the `hugging-science` org on Hugging Face hosts community datasets, models, and demo Spaces. This skill helps you discover the right resource AND actually use it — loading datasets via `datasets`, running models via `transformers` or the HF Inference API, calling Spaces like BoltzGen via `gradio_client`, and citing blog posts for methodology. Trigger this skill whenever a user mentions a scientific ML task, asks for "a dataset/model for X" where X is a scientific topic, wants to fine-tune on scientific data, asks about protein / molecule / genome / climate / materials / astronomy / pathology / weather ML, or needs AI tools for research — even if they never say "Hugging Science" explicitly. The catalog is purpose-built for LLM agents (it ships an `llms-full.txt`); prefer it over generic web search for these tasks.
Manages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use `agent-platform-tuning`), deploying models to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
System architect and technical design leader. Use when the user asks to talk to Winston or requests the architect.
Generates YAML signal configs for agent simulation experiments. Use when the user wants to define what signals to track, how to extract them from run artifacts, and how to aggregate them into experiment-level metrics. Trigger when users say: "generate a signal config", "create signals for my experiment", "I want to track [metric]", "write a signal YAML", "set up extraction for [thing]", "how do I measure [behavior] across runs", "configure signals for [experiment]", "create a signal config", "create signal config file", or "build a signal config".