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by io.github.whiteknightonhorse
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Canada Open Data Subject List

open-canada.reference.subject_list
Read-onlyIdempotent

List the Government of Canada open data subject taxonomy (e.g. "health_and_safety", "nature_and_environment") with the current dataset count per subject, optionally filtered by a substring. Use the returned subject slug as the subject filter for open-canada.dataset_search. Data: open.canada.ca CKAN Action API, no auth required.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "open-canada.reference.subject_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNoSubstring filter on subject slug (e.g. "health")

Output Schema

NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. Added
  6. Removed
  7. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, covering safety. The description adds useful context beyond annotations: it states the data source (open.canada.ca CKAN Action API) and that no auth is required. It also discloses the output includes dataset counts per subject, which is behavioral detail. This is sufficient for a read-only reference tool.

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?

Three sentences, each earning its place: the first states what the tool does, the second explains how to use the output (as a filter for dataset_search), and the third gives the data source and auth status. Information is front-loaded and there is 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?

For a simple taxonomy list tool with an output schema, the description covers the core function, the filter parameter, downstream usage, and data source. It does not mention pagination or rate limits, but for a taxonomy list these are likely minor. The presence of an output schema means return values need not be detailed. Overall, an agent has enough to call this tool correctly.

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?

The single parameter 'query' is fully described in the schema (substring filter on subject slug). The description reinforces this with examples (e.g., 'health') and clarifies it is optional, but does not add substantial new meaning beyond the schema. Since schema coverage is 100%, a baseline of 3 is appropriate; the description adds marginal value.

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 (List), the resource (Government of Canada open data subject taxonomy), and the output (subjects with dataset counts). It also distinguishes itself from the sibling dataset search tools by explicitly noting the returned slug is used as a filter for open-canada.dataset_search. The examples of slugs make the purpose unambiguous.

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?

It provides clear guidance on when to use this tool (to get subject taxonomy for filtering dataset searches) and even names the downstream tool (open-canada.dataset_search). It does not explicitly contrast with sibling reference tools like open-canada.reference.organization_list, but the purpose is specific enough that an agent would not confuse them.

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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