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AI工程师

Skills specifically designed for AI engineers to help you develop, test, and deploy AI applications more efficiently

解决的痛点

Frequent context switching between different AI models and frameworks for testing

Time-consuming code debugging and performance optimization

Tedious data processing and preprocessing workflows

Lack of unified toolchain for model deployment and monitoring

Need to quickly prototype and validate ideas and experiments

Documentation and knowledge sharing takes significant time

推荐 Skills

Agent Builder

Design and build AI agents for any domain. Use when users:(1) ask to "create an agent", "build an assistant", or "design an AI system"(2) want to understand agent architecture, agentic patterns, or autonomous AI(3) need help with capabilities, subagents, planning, or skill mechanisms(4) ask about Claude Code, Cursor, or similar agent internals(5) want to build agents for business, research, creative, or operational tasksKeywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration

14231
agent-design autonomous-ai workflow-automation ai-architecture business-processes tool-orchestration multi-step-reasoning agent-systems

作者: shareAI-lab

AutoGPT Agents - 构建自主AI工作流

使用可视化工作流构建和部署自主AI代理。无需编码即可创建连续执行代理、多步骤自动化系统和持久化AI工作流。非常适合希望自动化复杂业务流程的产品经理。

16036
autonomous-agents visual-builder workflow-automation ai-platform no-code multi-agent continuous-execution webhooks

作者: davila7

Claude Opus 4 5 Migration

Migrate prompts and code from Claude Sonnet 4.0, Sonnet 4.5, or Opus 4.1 to Opus 4.5. Use when the user wants to update their codebase, prompts, or API calls to use Opus 4.5. Handles model string updates and prompt adjustments for known Opus 4.5 behavioral differences. Does NOT migrate Haiku 4.5.

56596
claude-migration opus-4-5 api-upgrade model-transition codebase-migration anthropic-api prompt-optimization

作者: anthropics

Cocoindex

Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.

16036
etl data-transformation vector-database embeddings knowledge-graph ai-pipeline incremental-processing real-time

作者: davila7

Crewai Multi Agent

Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.

16036
multi-agent autonomous crewai orchestration collaboration workflows role-based production

作者: davila7

Langsmith Observability

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

16036
observability tracing evaluation monitoring debugging llm-ops testing langsmith

作者: davila7

Skill Development

This skill should be used when the user wants to "create a skill", "add a skill to plugin", "write a new skill", "improve skill description", "organize skill content", or needs guidance on skill structure, progressive disclosure, or skill development best practices for Claude Code plugins.

56596
skill-development claude-plugins documentation ai-specialization workflow-automation progressive-disclosure technical-writing plugin-architecture

作者: anthropics

Tool Design

This skill should be used when the user asks to "design agent tools", "create tool descriptions", "reduce tool complexity", "implement MCP tools", or mentions tool consolidation, architectural reduction, tool naming conventions, or agent-tool interfaces.

7006
agent-tools api-design tool-consolidation mcp architecture developer-experience ai-agents context-engineering

作者: muratcankoylan

Data Pipeline Builder

4.7

Automate data processing pipeline construction with support for multiple data sources and transformations

4500
310
Data Processing ETL Automation 数据工程师ing

作者: DataFlow

ML Model Debugger

4.6

Quickly diagnose machine learning model issues with detailed debugging info and fix suggestions

3800
280
Machine Learning Debugging Model Optimization TensorFlow PyTorch

作者: AI Tools

Python Code Analyzer

4.8

Intelligently analyze Python code quality, provide optimization suggestions and best practices

5200
156
Python Code Quality Optimization Best Practices

作者: CodeMaster

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