Total 50,553 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
Google Gemini embeddings API (gemini-embedding-001) for RAG and semantic search. Use for vector search, Vectorize integration, or encountering dimension mismatches, rate limits, text truncation.
Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.
Transform the voice in an audio recording into a different target voice while preserving emotion, timing, and delivery using the ElevenLabs Voice Changer (speech-to-speech) API. Use when converting one voice to another, changing the speaker/narrator of an existing recording, dubbing a voice-over in a different voice, creating character voices from a scratch performance, anonymizing a speaker, or any "voice conversion / voice transfer / speech-to-speech" task. Make sure to use this skill whenever the user mentions voice changing, voice conversion, speech-to-speech, swapping a voice in audio, re-voicing a clip, or applying a different voice to an existing recording — even if they don't explicitly say "voice changer".
Detect new or modified skills in .agents/skills/ by comparing git hashes against ai-skills, snapshot for rollback, review, publish to ai-skills, install locally, and cherry-pick lockfile to TARGET. Replaces /elevate-skill.
Adapt an ML paper's writing, structure, positioning, and paragraph-level narrative to a target conference such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or similar venues. Use this skill whenever the user wants to submit, rewrite, polish, restructure, or tailor a paper for a specific conference; asks what good accepted/oral papers at a venue look like; wants reviewer-friendly writing; or wants section-by-section or paragraph-by-paragraph paper guidance. This is a writing and presentation skill, not an experiment-design skill.
Create an AI persona from scratch. Interactive guidance: Enter persona name → Provide materials (URL/file/pasted text) → Automatic distillation → Output a directly usable skill directory. Activate when: User says /create-soul, "创建人物", "蒸馏 [某人]", "create a persona for [name]".
Install and manage AI agent skills from Python/JS libraries so agents always use up-to-date patterns
Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.
Use when extracting imperatives from agent instruction files, analyzing rule coverage, or preparing input for /policy-algebra and /distill.
Novel content polishing and optimization, suitable for user requests such as "Help me polish this novel", "Improve the writing style", "Optimize chapter rhythm", "Enhance this highlight", "Make dialogues more natural", "Make this passage more engaging", "Optimize novel writing style", "Adjust chapter rhythm", "Make dialogues more realistic", "Help me revise this content", "Polish novel", "Optimize highlights", "Improve writing style", "Make this passage more immersive", etc. It provides 3 levels of polishing, focusing on optimization of writing style and content, supporting special optimizations such as style adaptation, rhythm tightening, highlight enhancement, dialogue optimization, etc. **Polished results directly modify the chapters/ directory, and automatic backups are made to .sumeru/write/original/ before modification**. **Sub-Agents are used for parallel processing during batch polishing, with each Agent responsible for a maximum of 3 chapters**
Structured medical case presentation for clinical rounds, conferences, and documentation. Generates SOAP-format or narrative case reports with physiologically accurate vitals, labs, and evidence-based plans. Use when the brief mentions "case report", "case presentation", "SOAP note", "clinical case", "ward rounds", "case summary", or "patient presentation".
Use for tasks that may need brief clarification before implementation but don't warrant a full plan. If clear, dispatches an implementer immediately; if unclear, asks 1-3 questions, proposes an approach, gets approval, then dispatches. No plan file — lighter and faster than nash + stoudemire.