Total 50,613 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
You are **AgentsOrchestrator**, the autonomous pipeline manager who runs complete development workflows from specification to production-ready implementation. You coordinate multiple specialist age...
Brain knowledge base operations. The core read/write cycle: brain-first lookup, read-enrich-write loop, source attribution, ambient enrichment, back-linking. Read this before any brain interaction.
Agent-driven physical Texas Hold'em robot skill. Uses per-state image/action folders, visual guidelines, durable hole-card and action-sequence caches, and deterministic helpers for capture, state updates, command translation, and robot execution. Use for running or maintaining this DexHoldem workflow with Codex, Claude Code, or another coding agent.
Short-form video generation skill — 3-10 second clips for product reveals, motion teasers, ambient loops. Defaults to Seedance 2 but works the same with Kling 3 / 4, Veo 3 or Sora 2. Output is one MP4 saved to the project folder. When the workspace also ships an interactive-video / hyperframes skill, prefer composing several short shots into a single timeline rather than one long monolithic clip.
Phân tích sâu bất kỳ chủ đề nào qua lăng kính Lý thuyết Trò chơi (Game Theory).
Step-by-step analysis for complex problems — multi-step reasoning, hypothesis verification, adaptive planning with revision.
This skill should be used when implementing, consuming, or debugging an Open Responses-compliant API — the open standard for multi-provider LLM interoperability. Covers protocol, items, state machines, streaming events, tools, the agentic loop pattern, and extensions. Triggers on: Open Responses, open-responses, /v1/responses endpoint, multi-provider LLM API, Open Responses compliance.
Skills for Upstash Vector features, TypeScript/JavaScript SDK usage, and integrations. Use when users ask how to work with Vector, its TS SDK, features, or supported frameworks.
Capture the current task into a structured temporary session bundle under `.agents/sessions/` so a learning agent can later distill durable repo knowledge. Use for completed, blocked, or abandoned tasks with meaningful changes, debugging, validation, or reusable lessons.
Guide a focused CS or AI literature review sprint that turns a topic, idea, claim, or project direction into a ranked paper map, closest-work risk assessment, method taxonomy, novelty implications, baseline implications, and next actions. Use this skill whenever the user needs to survey a topic, check novelty, map related work, prepare a project, find canonical or recent papers, decide read/skim/ignore priority, or turn papers into a research direction.
Diagnose surprising, negative, unstable, or ambiguous ML/AI experiment results and decide whether to debug implementation, rerun experiments, change metrics or baselines, revise the algorithm, narrow the paper claim, park, or kill a direction. Use this skill whenever results do not match expectations, a method fails, metrics conflict, seeds vary, baselines beat the method, plots look suspicious, or the user asks what to do next after experimental results.
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript.