Total 43,771 skills, AI & Machine Learning has 6986 skills
Showing 12 of 6986 skills
DigitalOcean Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents on GPU infrastructure with foundation models, knowledge bases, and agent routes. Use when planning or operating AI agents on DigitalOcean.
Save a concise handoff summary only when the user explicitly requests it. Use this for resumable progress notes in generic agent environments where a real session importer is not guaranteed.
Baidu AI Search. Supports four modes: web search, Baidu Encyclopedia, Miaodong Encyclopedia, and AI intelligent generation. Automatically includes current date context. Used when users request information search, encyclopedia queries, latest news acquisition, news search, and data lookup.
Forces adversarial reasoning before committing to decisions. Triggers on architectural choices, approach selection, and planning phases to prevent premature commitment bias.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Analyze a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code for a project, or wants to know what Claude Code features they should use.
Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.
Connect Claude to any app. Send emails, create issues, post messages, update databases - take real actions across Gmail, Slack, GitHub, Notion, and 1000+ services.
OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.
Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, or context augmentation.
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.