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OpenClaw Skills & Use Case Index

ClawIndex is an ecosystem-driven index of OpenClaw skills and real-world use cases.

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Skills with input: LLM model

Browse skills that use this input.

  • neuron-agent-builder - Neuron AI Agent Builder for PHP
    agent builderPHPtoolsstreaming

    ★ 121 · Updated 2026-05-28

    Create and configure Neuron AI agents with providers, tools, instructions, and memory.

    ⚙ create agents⚙ configure providers⚙ define instructions
  • llm-benchmark - LLM Benchmark Design and Optimization
    benchmarkingLLMtestingstatistical analysis

    ★ 21 · Updated 2026-05-28

    Guide for designing, running, and interpreting LLM benchmark experiments with statistical analysis and data leakage prevention

    ⚙ design test suites⚙ run benchmark experiments⚙ compare prompt variants
  • tensorrt-llm - TensorRT-LLM LLM Inference Optimization
    Inference ServingTensorRT-LLMNVIDIAInference Optimization

    ★ 2 · Updated 2026-03-19

    Optimizes LLM inference with NVIDIA TensorRT for high-throughput, low-latency production deployment on NVIDIA GPUs.

    ⚙ optimize LLM inference⚙ compile models with TensorRT⚙ serve models via HTTP API
  • langgraph - Build stateful agent graphs
    workflowgraphagentstateful

    ★ 650 · Updated 2026-03-19

    Build stateful agent graphs with checkpoints and conditional flows

    ⚙ create StateGraph objects⚙ write node functions⚙ add edges
  • prompt-engineer - Expert prompt engineering for optimal LLM performance
    prompt-engineeringLLM-optimizationAI-developmentmodel-performance

    ★ 15 · Updated 2026-03-09

    Design, optimize and evaluate prompts to maximize LLM performance across diverse use cases

    ⚙ Design prompt patterns⚙ Create evaluation frameworks⚙ Test prompts systematically
  • prompting - Prompt Engineering and Context Optimization for AI Agents
    prompt-engineeringcontext-engineeringai-agentsllm-optimization

    ★ 1 · Updated 2026-02-15

    Provides prompt engineering standards and context engineering principles for AI agents.

    ⚙ create prompt structures⚙ optimize token usage⚙ design context engineering