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Datasets

datasets
Read-onlyIdempotent

Search the ENERGY STAR Open Data catalog of open datasets by keyword. Returns each dataset's resource_id, name, description, category and update date — pass the resource_id to query/metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax datasets (1-100, default 20).
queryNoKeyword to search dataset titles/descriptions (e.g. "budget", "crime", "health").
offsetNoPagination offset.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "query": "energy efficiency"
      +  },
      +  {
      +    "limit": 10,
      +    "offset": 0,
      +    "query": "building performance"
      +  }
      +]
  2. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by specifying the return fields (resource_id, name, description, category, update date) and recommending follow-up actions, but does not disclose rate limits or auth requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the main action (keyword search) and return information, with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple search tool with full schema coverage and annotations, the description covers the purpose, return fields, and a follow-up hint. It is sufficiently complete for an agent to understand usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers all three parameters with descriptions (100% coverage). The description does not add additional meaning beyond what the schema provides, meeting the baseline for full schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches the ENERGY STAR Open Data catalog by keyword and returns specific fields. The verb 'Search' and resource are explicit, and it distinguishes from siblings by focusing on dataset search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for searching datasets and suggests passing resource_id to query/metadata, but it does not explicitly compare to siblings or state when to use this tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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