Aard

Inspect a staged statistical dataset

inspect_dataset

Read-onlyIdempotent

Return cached columns/types and row count, never observation rows.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dataset_id": "<dataset_id>"
    },
    "name": "inspect_dataset"
  }
}

Input Schema

Name	Required	Description	Default
`dataset_id`	Yes	Id returned by stage_url
`response_format`	No	How the column table is sent. "auto" (default) means no preference and lets the server decide; "text" sends it as CSV only — in the text content, and in structuredContent as a "csv" string in place of typed columns. "structured" sends typed fields only, "both" the CSV and the typed fields. If you got a summary but no column table, call again with response_format="text".	auto

Output Schema

Name	Required	Description	Default
`csv`	No
`columns`	No
`row_count`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 30, 2026

changedInput schema / properties / response_format / description

Previous value: -"Which channel carries the column table. \"auto\"\n(default) means no preference and lets the server decide; \"text\"\nsends it as CSV in the text channel only, \"structured\" as typed\nfields only, \"both\" in both. If you got a summary but no column\ntable, call again with response_format=\"text\"."New value: +"How the column table is sent. \"auto\" (default)\nmeans no preference and lets the server decide; \"text\" sends it as\nCSV only — in the text content, and in structuredContent as a\n\"csv\" string in place of typed columns. \"structured\" sends typed\nfields only, \"both\" the CSV and the typed fields. If you got a\nsummary but no column table, call again with\nresponse_format=\"text\"."

addedOutput schema / properties / csv
```
Added value: +{
+  "type": "string"
+}
```

Changed2 schema fields changedSep 28, 2026

addedInput schema / properties / dataset_id / description
```
Added value: +"Id returned by stage_url"
```

addedInput schema / properties / response_format / description

Added value: +"Which channel carries the column table. \"auto\"\n(default) means no preference and lets the server decide; \"text\"\nsends it as CSV in the text channel only, \"structured\" as typed\nfields only, \"both\" in both. If you got a summary but no column\ntable, call again with response_format=\"text\"."

First observedSep 15, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so safety and repeatability are covered. The description adds useful scope disclosure ('cached' metadata, no observation rows), but says nothing about staleness of the cache, error behavior for a bad dataset_id, or lifecycle relative to release_dataset.

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?

A single front-loaded sentence naming the returned artifacts and the excluded ones. No filler and no redundancy with the title.

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?

An output schema exists, so return values need no elaboration, and the description correctly summarizes what is returned. For a two-parameter read-only metadata tool this is largely sufficient, with the only gap being the stage_url-to-dataset_id prerequisite and cache staleness.

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?

Schema description coverage is 100%, including a detailed response_format enum with a recovery instruction, so the schema does all the work. The description adds no parameter meaning beyond it, which is the expected baseline when coverage is complete.

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

Purpose4/5

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

States a concrete verb+resource (inspect a staged dataset) and enumerates the exact payload: cached columns/types plus row count. The clause 'never observation rows' implicitly separates it from row-returning siblings such as query_dataset, though it never names that sibling explicitly.

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?

Usage is only implied: 'never observation rows' suggests you use this for schema/shape checks and query_dataset for actual data, but no when-to-use or when-not-to-use condition is stated. The one actionable fallback hint (retry with response_format="text") lives in the schema, not the description.

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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