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Glama

Query

query
Read-onlyIdempotent

Run a Socrata SoQL query against a Utah Open Data dataset by resource_id (e.g. "7n5d-er3z"). 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. "7n5d-er3z" (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": "7n5d-er3z",
      +    "where": "year >= 2020"
      +  },
      +  {
      +    "group": "name",
      +    "order": "count DESC",
      +    "resource_id": "7n5d-er3z",
      +    "select": "name, count(*) AS count"
      +  }
      +]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already mark the tool read-only, idempotent, and non-destructive. The description adds that the tool returns JSON rows, uses SoQL clauses, and supports pagination (limit/offset). This adds value beyond annotations, but does not disclose potential rate limits or other edge-case behaviors.

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, front-loaded with the primary action and resource. No filler, every phrase is necessary and informative. Excellent conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite 7 parameters and no output schema, the description covers the core use case: querying by resource_id with SoQL and pagination, and returns JSON. Examples in the schema fill any remaining gaps. Complete for its complexity level.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions per parameter. The description adds critical context: SoQL clauses must omit the leading '$', includes an example for each clause, and clarifies limit/offset pagination. This significantly enhances understanding beyond the raw schema.

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 states the tool runs a Socrata SoQL query against a Utah Open Data dataset by resource_id, specifies the return format (JSON), and distinguishes from siblings like 'datasets' (likely lists datasets) and 'search_within' (different search), leaving no ambiguity.

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 explicitly says to use 'where/select/group/order' and 'limit/offset' with SoQL clauses, giving clear syntax guidance. It implicitly indicates that the tool is for querying data by resource_id, but does not explicitly contrast with sibling tools like 'datasets' or 'search_within', so it's slightly lacking for alternative exclusion.

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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TDQS

A3.8/5.0
Disambiguation2/5

The toolset contains several near-duplicate clusters: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route the same kinds of questions, and the six polymarket tools have heavily overlapping scopes. An agent would frequently struggle to pick the right variant despite the detailed descriptions.

Naming Consistency4/5

Names consistently use lowercase snake_case with a verb-first or domain-prefixed pattern (ask_pipeworx, resolve_entity, validate_claim, polymarket_arbitrage). Minor deviations like bare nouns (datasets, metadata) are acceptable but not perfectly uniform.

Tool Count2/5

34 tools is far beyond what a Utah Open Data server needs; only 3 tools actually relate to the named domain. The rest form a sprawling general-purpose Pipeworx/prediction-market platform, making the surface feel bloated for its stated purpose.

Completeness3/5

For the actual Utah Open Data catalog, datasets/query/metadata is a complete read-only surface. But for the broader Pipeworx functionality the set actually delivers, there are odd gaps (no account management beyond subscriptions) and many irrelevant tools, so overall coverage is uneven.