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Glama

Data Winnipeg

by io.github.pipeworx-io
OverviewAdmin

Query

query
Read-onlyIdempotent

Run a Socrata SoQL query against a Winnipeg Open Data dataset by resource_id (e.g. "d4mq-wa44"). 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. "d4mq-wa44" (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: +[
+  {
+    "resource_id": "d4mq-wa44"
+  },
+  {
+    "limit": 50,
+    "order": "count DESC",
+    "resource_id": "d4mq-wa44",
+    "select": "name, count(*) AS count",
+    "where": "year >= 2020"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already provide readOnly, idempotent, and non-destructive hints. Description adds that output is JSON and explains SoQL clause formatting, but doesn't cover rate limits or pagination details beyond limit/offset. Adequate given annotation coverage.

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 efficient sentences with no fluff. First sentence states core action, second adds details. Fully 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 tool with full schema coverage and no output schema, description adequately covers parameter usage and return format. Could mention that results are JSON array, but overall sufficient.

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 covers all 7 parameters with descriptions. Description adds value by clarifying that SoQL clauses are used without leading '$' and that limit defaults to 1000, going beyond schema explanations.

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?

Description clearly states the tool runs SoQL queries against a Winnipeg Open Data dataset by resource_id, mentions key parameters, and returns JSON. It distinguishes from siblings like 'datasets' by focusing on querying rather than listing.

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?

Description indicates when to use (for filtering/aggregating data) and provides examples. It does not explicitly mention alternatives or when not to use, but the context of sibling tools makes the purpose 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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