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AgentNative: Public Data, Government Datasets, Federal Statistics & Official Records

List queryable official datasets

list_imported_datasets
Read-onlyIdempotent

Use this free tool when an agent needs only datasets that can be sampled or queried now. Returns fully published warehouse snapshots with dataset IDs, row counts, freshness, and provenance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already provide readOnly, idempotent, and non-destructive safety traits. The description adds useful behavioral context by specifying that it returns 'fully published warehouse snapshots' with dataset IDs, row counts, freshness, and provenance, which helps the agent understand what the response contains.

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 concise sentences, with the core usage condition front-loaded. Every sentence adds value: the first tells when to call it, the second tells what it returns. No wasted words.

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

Completeness5/5

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

For a zero-parameter, read-only listing tool, the description is complete. It covers purpose, usage condition, and return contents, and the sibling list provides surrounding context. No output schema exists, but the description gives enough return-value information.

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

Parameters4/5

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

There are zero parameters, so the baseline is 4. The description has nothing to add about parameters and does not need to; the input schema already covers the complete parameter set.

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 uses a specific verb ('list') and a precise resource ('datasets that can be sampled or queried now'). It clearly distinguishes itself from siblings by narrowing scope to queryable/sampleable official datasets only, rather than all discovered or official sources.

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

Usage Guidelines4/5

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

It explicitly states when to use the tool: 'Use this free tool when an agent needs only datasets that can be sampled or queried now.' It does not name alternative tools directly, but the 'only' condition and the sibling tool names make routing fairly clear.

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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