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by io.github.pipeworx-io
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Query

query
Read-onlyIdempotent

Query records from a SNCF Open Data dataset with ODSQL. Filter (where), aggregate (group_by/select), sort (order_by), paginate (limit/offset).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax records (1-100, default 20).
queryNoFree-text keyword across all fields (optional).
whereNoODSQL filter, e.g. `year >= 2020 AND city = "Paris"` (overrides query).
offsetNoPagination offset (default 0).
selectNoODSQL select/aggregation, e.g. `count(*) as n, sum(amount)`.
group_byNoODSQL group_by field(s).
order_byNoSort, e.g. `date desc`.
dataset_idYesDataset id from search_datasets.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "dataset_id": "sncf-open-data-train-schedules",
+    "limit": 50,
+    "where": "year >= 2020"
+  },
+  {
+    "dataset_id": "sncf-open-data-punctuality",
+    "group_by": "station",
+    "order_by": "avg_delay desc",
+    "select": "count(*) as total, avg(delay_minutes) as avg_delay"
+  }
+]
  2. 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, so the description is not burdened with safety disclosure. The description adds value by detailing the query language (ODSQL) and supported clauses (filter, aggregate, sort, paginate), enhancing understanding of capabilities beyond 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?

The description is a single sentence that front-loads the core purpose and succinctly lists supported operations with parenthetical grouping. Every word is necessary and no 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?

With no output schema, the description omits the return format, but for a query tool the return of records is implicit. It covers all major functional aspects (filter, aggregate, sort, paginate) and the prerequisite of specifying a dataset_id. Sufficient for most use cases given good annotations.

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?

All 8 parameters are fully described in the input schema (100% coverage). The description groups parameters into conceptual categories (filter, aggregate, sort, paginate) but does not add new semantic details beyond the schema. 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 states the verb 'Query', the resource 'SNCF Open Data dataset', and the specific ODSQL operations (filter, aggregate, sort, paginate). This distinguishes it from sibling tools like 'search_datasets' which find datasets, not query records.

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 implies usage for querying data with ODSQL, but does not explicitly state when to use this tool versus alternatives like 'search_datasets' or 'search_within'. No exclusions or comparative guidance are provided.

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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