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All Skills

Total 31,117 skills, AI & Machine Learning has 5036 skills

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Showing 12 of 5036 skills

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AI & Machine Learningterrylica/cc-skills

hooks-development

Claude Code hooks development guide. TRIGGERS - create hook, PostToolUse, PreToolUse, Stop hook, hook lifecycle, decision block.

🇺🇸|EnglishTranslated
1
AI & Machine Learningterrylica/cc-skills

slash-command-factory

Generate custom Claude Code slash commands via guided question flow. TRIGGERS - create slash command, generate command, custom command.

🇺🇸|EnglishTranslated
1
2 scripts/Attention
AI & Machine Learningterrylica/cc-skills

mlflow-python

MLflow experiment tracking via Python API. TRIGGERS - MLflow metrics, log backtest, experiment tracking, search runs.

🇺🇸|EnglishTranslated
1
4 scripts/Checked
AI & Machine Learningterrylica/cc-skills

ml-failfast-validation

POC validation patterns to catch issues before committing to long-running ML experiments. TRIGGERS - fail-fast, POC validation, preflight check, experiment validation, schema validation, gradient check, sanity check, smoke test.

🇺🇸|EnglishTranslated
1
AI & Machine Learningyonatangross/orchestkit

langgraph-streaming

LangGraph streaming patterns for real-time updates. Use when implementing progress indicators, token streaming, custom events, or real-time user feedback in workflows.

🇺🇸|EnglishTranslated
1
AI & Machine Learningyonatangross/orchestkit

langgraph-supervisor

LangGraph supervisor-worker pattern. Use when building central coordinator agents that route to specialized workers, implementing round-robin or priority-based agent dispatch.

🇺🇸|EnglishTranslated
1
2 scripts/Attention
AI & Machine Learningyonatangross/orchestkit

langgraph-tools

LangGraph tool calling patterns. Use when binding tools to LLMs, implementing ToolNode for execution, dynamic tool selection, or adding approval gates to tool calls.

🇺🇸|EnglishTranslated
1
AI & Machine Learningyonatangross/orchestkit

langgraph-parallel

LangGraph parallel execution patterns. Use when implementing fan-out/fan-in workflows, map-reduce over tasks, or running independent agents concurrently.

🇺🇸|EnglishTranslated
1
1 scripts/Attention
AI & Machine Learningyonatangross/orchestkit

mcp-server-building

Building MCP (Model Context Protocol) servers for Claude extensibility. Use when creating MCP servers, building custom Claude tools, extending Claude with external integrations, or developing tool packages for Claude Desktop.

🇺🇸|EnglishTranslated
1
AI & Machine Learningyonatangross/orchestkit

langgraph-checkpoints

LangGraph checkpointing and persistence. Use when implementing fault-tolerant workflows, resuming interrupted executions, debugging with state history, or avoiding re-running expensive operations.

🇺🇸|EnglishTranslated
1
AI & Machine Learningyonatangross/orchestkit

langgraph-state

LangGraph state management patterns. Use when designing workflow state schemas, using TypedDict vs Pydantic, implementing accumulating state with Annotated operators, or managing shared state across nodes.

🇺🇸|EnglishTranslated
1
AI & Machine Learningyonatangross/orchestkit

langgraph-routing

LangGraph conditional routing patterns. Use when implementing dynamic routing based on state, creating branching workflows, or building retry loops with conditional edges.

🇺🇸|EnglishTranslated
1
1 scripts/Checked
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