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Query

query
Read-onlyIdempotent

Run a Socrata SoQL query against a Nova Scotia Open Data dataset by resource_id (e.g. "3nka-59nz"). 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. "3nka-59nz" (from datasets).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "limit": 50,
      +    "resource_id": "3nka-59nz",
      +    "where": "year >= 2020"
      +  },
      +  {
      +    "group": "category",
      +    "order": "total DESC",
      +    "resource_id": "3nka-59nz",
      +    "select": "name, count(*) AS total"
      +  }
      +]
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that results are returned as JSON and that SoQL clauses should omit the leading '$', which is helpful but does not go beyond the annotation coverage. No contradictions.

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?

The description is a single, well-structured sentence that front-loads the core purpose and immediately provides essential usage details (resource_id, clauses, return format). No extraneous words or redundancy.

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?

Given the tool's complexity (7 parameters, 1 required, no output schema), the description covers the main usage pattern and return format. It omits details like error handling or pagination behavior beyond 'limit/offset', but the schema provides defaults. The annotations further reduce the need for extra behavioral context.

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 described. The description adds value by noting that SoQL clauses should be written without the leading '$', which is not in the schema. However, it does not significantly enhance the schema's existing explanations. Baseline 3 is appropriate.

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 specifies the tool's purpose: running a Socrata SoQL query against a specific dataset identified by resource_id. It details the main filtering clauses (where, select, group, order, limit, offset) and gives an example resource_id. This specificity distinguishes it from sibling tools like 'datasets' (which lists datasets) and other query tools.

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 states what the tool does but provides no explicit guidance on when to use it versus alternatives (e.g., 'search_within' or 'datasets'). It lacks 'when-not-to-use' instructions or comparisons, relying on the user to infer its applicability from the purpose.

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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