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Query

query
Read-onlyIdempotent

Run a Socrata SoQL query against a Sonoma County Open Data dataset by resource_id (e.g. "3rsj-iche"). Filter with where/select/group/order (SoQL clauses, without the leading $) plus limit/offset. Returns matching rows as JSON.

Input Schema

TableJSON 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. "3rsj-iche" (from datasets).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "limit": 50,
      -    "resource_id": "3rsj-iche",
      -    "where": "year >= 2020"
      -  }
      -]New value: +[
      +  {
      +    "limit": 20,
      +    "resource_id": "3rsj-iche"
      +  }
      +]
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "limit": 50,
      +    "resource_id": "3rsj-iche",
      +    "where": "year >= 2020"
      +  }
      +]
  3. 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=false, covering the safety profile. The description adds meaningful behavioral detail: SoQL clauses must omit the leading $, results come back as JSON, and limit/offset support pagination, which goes beyond the schema.

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 with no filler: the first states the core operation and target resource, the second covers supported clauses and result format. All information is relevant and front-loaded.

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 read-only query tool with fully documented parameters and no output schema, the description covers invocation, query construction, pagination, and response format. It doesn't explain SoQL edge cases or error behavior, but those are not essential for selecting and invoking the tool correctly.

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%, with each parameter already documented with examples and context. The description adds only a small amount of global syntax guidance (omit the leading $) and reinforces pagination, which is marginal beyond what the schema already provides.

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 specific action (run a SoQL query) against a specific resource (Sonoma County Open Data dataset identified by resource_id), and clarifies it returns rows as JSON. It is distinguishable from siblings like datasets or metadata by focusing on data content rather than dataset discovery, though it doesn't explicitly name a sibling.

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?

Clear context: use this when you have a resource_id and need to filter, select, group, or order rows from a dataset. It implies using datasets first to obtain the resource_id, but it does not explicitly state when not to use it or name alternatives like datasets or metadata.

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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