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Data Vermont

by io.github.pipeworx-io
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Query

query
Read-onlyIdempotent

Run a Socrata SoQL query against a Vermont Open Data dataset by resource_id (e.g. "jgqy-2smf"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

Input Schema

NameRequiredDescriptionDefault
groupNoSoQL $group column(s).
limitNoMax rows (default Socrata 1000).
orderNoSoQL $order, e.g. "date DESC".
whereNoSoQL $where filter, e.g. "year >= 2020 AND status = 'Active'".
offsetNoPagination offset.
selectNoSoQL $select, e.g. "name, count(*) AS n".
resource_idYesDataset id, e.g. "jgqy-2smf" (from datasets).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "limit": 100,
-    "resource_id": "jgqy-2smf",
-    "where": "year >= 2020"
-  },
-  {
-    "group": "name",
-    "order": "total DESC",
-    "resource_id": "jgqy-2smf",
-    "select": "name, count(*) AS total"
-  }
-]New value: +[
+  {
+    "limit": 20,
+    "resource_id": "jgqy-2smf"
+  },
+  {
+    "limit": 20,
+    "resource_id": "jgqy-2smf",
+    "select": "name"
+  }
+]
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "limit": 100,
+    "resource_id": "jgqy-2smf",
+    "where": "year >= 2020"
+  },
+  {
+    "group": "name",
+    "order": "total DESC",
+    "resource_id": "jgqy-2smf",
+    "select": "name, count(*) AS total"
+  }
+]
  3. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare the operation read-only, idempotent, and non-destructive, so the description does not need to restate safety. It adds useful behavioral context by noting that SoQL clauses must be passed without the leading '$' and that results are returned as JSON rows, which are not encoded in the annotations.

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 carry all essential information with no filler. The primary action and target are front-loaded, followed by the compact SoQL clause list and return format.

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?

The description is complete enough for a no-output-schema tool: it names the target dataset, the query language, the supported clauses, and the JSON return format. It does not elaborate on default limits or the exact result shape, but the input schema covers defaults and the returned JSON rows are adequately described.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining the collective query pattern and explicitly warning that soql clauses are passed without the leading '$', a likely source of invocation errors. It also clarifies the role of resource_id as the dataset selector.

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 states a specific verb ('Run'), a specific resource ('Socrata SoQL query against a Vermont Open Data dataset by resource_id'), and the supported operation pattern. It clearly differentiates this tool from sibling tools like datasets or metadata, which are about discovery rather than row-level querying.

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?

The description clearly communicates when this tool is appropriate: when the agent needs to query dataset rows using SoQL clauses. It does not explicitly name alternative tools or state exclusions, but the context of the sibling list and the resource_id-by-dataset framing imply the correct usage.

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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