AssetOpsBench Transformer Scenarios: 50 Smart Grid Tasks for LLM Agents

50 structured natural-language evaluation scenarios for LLM-based AI agents operating on industrial Smart Grid Transformer assets. The dataset was created by author rohithkanathur and last updated on May 8, 2026. Each scenario requires an agent to answer by invoking one or more MCP tools across specialized servers.

Use Cases

• Benchmarking LLM agent performance on industrial asset management tasks based on structured scenarios.
• Testing multi-agent coordination based on described combinations of IoT, FMSR, TSFM, and Work Order servers.
• Evaluating tool invocation accuracy for MCP (Model Context Protocol) tools based on natural-language task descriptions.

Strengths

• Contains 50 distinct evaluation scenarios for systematic benchmarking.
• Scenarios are grounded and structured for specific industrial smart grid contexts.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

huggingface

Freshness

Last updated 2026-05-08 18:32:15; freshness should be verified.