数据分析、机器学习、LLM 应用、提示词设计（8854 个）
Build document search with AgentDB that finds related content by meaning. Store documents as numerical representations, combine similarity search with metadata filters, and retrieve relevant passages for systems that generate answers using source material.
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Build AI agents that retain conversation history, user preferences, and useful interaction patterns with AgentDB. The skill covers persistent storage, meaning memories survive between sessions, plus retrieval, context management, and ReasoningBank integration.
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Coordinates multiple AI agents with agentic-flow to run tasks in parallel or through dependent stages. It covers team communication structures, shared memory, workload balancing, failure recovery, and performance monitoring for complex workflows.
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Search document collections by meaning using embeddings, numerical representations of text. Compare text similarity, route queries among a few predefined patterns, and use a compressed search index when memory is limited.
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Coordinate background tasks with specialized agents for research, optimization, audits, and more. Use execution history, quality scores, success rates, and latency to guide agent selection, track performance, and check benchmark compliance.
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Store and retrieve knowledge across agent sessions with AgentDB. Organize memories into tiers, search learned patterns, combine related memories into context, and record causal links to support later work.
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Train, deploy, and manage neural networks with Flow Nexus in isolated E2B environments. Use custom architectures or ready-made templates, run predictions, monitor distributed training across multiple environments, and evaluate models before sharing them.
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Create AgentDB learning plugins that use recorded experience to improve agent decisions. Choose a learning method, store states, actions, and rewards, train models, and evaluate suggested actions through CLI and API workflows.
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Plan and implement a unified AgentDB memory backend for agents. Migrate SQLite and Markdown data, add HNSW indexing for similarity search, and support shared memory and SONA learning patterns while preserving compatibility with existing systems.
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Delegate complex work through a tree of Claude Code sub-agents. Each level uses its own working context and returns concise summaries, helping the coordinating agent manage research, verification, and synthesis without retaining every intermediate detail.
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Set up a realtime evaluation folder with a suitable shared harness, the framework that runs evaluations. Prepare prompts, tool definitions, realistic starter data, and a README, then validate the setup with evaluation and test runs.
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Creates self-contained HTML charts, tables, diagrams, and dashboards for display within a conversation. It keeps figures traceable to calculations and checks readability in light and dark themes, including narrow mobile layouts, before showing the page.
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Analyze CSV, Parquet, and JSON files to answer questions through grouping, joins, cleaning, time series, and charts. Chooses DuckDB or Polars and a suitable processing location based on the task and available memory.
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Build voice assistants and conversational characters with ElevenLabs. Configure voices, language models, and external tools, then connect conversations to a website widget or use Twilio integration for outbound phone calls.
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Build custom interactive charts, network diagrams, and maps with d3.js. Guides data-driven drawing, tooltips, zooming, animation, responsive sizing, and accessibility, with examples that work in plain JavaScript or frameworks such as React, Vue, and Svelte.
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Create and update dashboards with charts, metrics, and tables drawn from connected data sources or attached files. Link displayed values to their sources so readers can inspect queries, calculations, and freshness while reviewing business indicators or recurring reports.
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Design multi-agent workflows for research, reviews, and migrations. Organize work across different evidence sources, add independent checks, and combine findings while preserving source references, unresolved questions, and limits on what was examined.
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Provide Jarvis with a static catalog of system voices through the included voice_source.json file. This skill supplies reference data only; it does not provide a workflow for choosing voices, handling voice requests, or creating widgets.
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Create charts and dashboards with a consistent approach to chart selection, color validation, labels, and interaction. Includes a palette checker and accessibility rules for readable visualizations in both light and dark modes.
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Store conversation history and project material locally, then search by meaning and retrieve original text. Organize memories by person or project, track dated relationships and facts, and keep diary entries that connect work across sessions.
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Initialize a new MemPalace for AI memory through a guided setup process. The skill retrieves setup instructions for a configuration that uses ChromaDB as its data storage backend and follows the returned steps.
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Train and run Uni-Mol Tools models to predict molecular properties from CSV data. Organize experiments into projects, compare model performance, rank results, and manage storage through interactive commands or machine-readable JSON output.
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Manage Ollama models and run text generation, chat, and embeddings, which represent text as numerical vectors, through command-line requests. Check server status, inspect model details, and receive structured JSON output for agent workflows.
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Process 3D scan data with CloudCompare through text commands. Clean point clouds, collections of measured 3D points, extract ground surfaces, align scans, calculate distances, and convert or export point clouds and surface meshes in supported formats.
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