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Statcan Csv Url

statcan_csv_url
Read-onlyIdempotent

Return the StatCan-hosted URL for a full cube as a CSV download (doesn't fetch the file — hands back a direct URL).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoen | fr (default en).
product_idYesCube product ID.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYesResponse status from API
languageYesLanguage code
product_idYesCube product ID
download_urlYesStatCan-hosted CSV download URL

Schema Changelog

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

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive. The description adds behavioral context by stating it returns a URL and does not fetch the file, which is consistent and provides useful additional detail.

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 with no redundant information. Every word serves a purpose.

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 simple nature of the tool (returning a URL), and the presence of a likely output schema, the description is sufficiently complete. It could mention error handling or conditions, but not necessary for basic operation.

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 coverage is 100%, so baseline is 3. The description adds slight value by mentioning 'full cube' implying the URL is for the entire cube, but does not elaborate on parameter specifics beyond what the schema already provides.

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 'Return' and the resource 'StatCan-hosted URL for a full cube as a CSV download'. It explicitly distinguishes from likely siblings that fetch data by stating 'doesn't fetch the file — hands back a direct URL'.

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 when to use it (when you need the URL without downloading), but does not explicitly mention when not to use it or compare to alternatives like statcan_cube_data.

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

Several tools are near-duplicates: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, ask_pipeworx_grounded is the same router with an extra extraction pass, and deep_research/ask_pipeworx overlap for broad questions. The prediction-market tools and the StatCan series/cube/indicator tools also have fuzzy boundaries despite their detailed descriptions.

Naming Consistency3/5

Names consistently use snake_case, but the set mixes verb-first names (resolve_entity, validate_claim, subscribe) with domain-prefixed noun-first names (statcan_*, polymarket_*, pipeworx_*) and one-off names like ai_visibility_check and generate_llms_txt. The domain prefixes help navigation, but there is no single predictable pattern and the ask_pipeworx_* suffix variants break the prefix convention.

Tool Count2/5

38 tools is well beyond the 25+ threshold, and the server named Statcan carries only 8 StatCan-specific tools alongside general Pipeworx routing, prediction-market analysis, AI visibility, dependency scanning, memory, and subscription features. This feels like several servers merged into one rather than a well-scoped StatCan interface.

Completeness4/5

Within the apparent StatCan data-access scope, the surface is solid: listing cubes, metadata, cube data, vector series, headline indicators, CSV URLs, and change detection cover the core workflows. The broader Pipeworx/analysis layers also include discovery, grounded lookups, entity resolution, validation, subscriptions, and memory, with only minor gaps like server-side StatCan search and no way to execute on prediction-market signals.