Canada Economic Indicators MCP

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

With no annotations, the description carries the behavioral disclosure burden. It usefully states the exact dashboard outputs and signals a 'PRO' subscription constraint, but it does not describe auth requirements, rate limits, or error behavior beyond what the access_token schema implies.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single efficient sentence that lists the key return values. It is appropriately sized, though the leading 'PRO.' is not front-loaded purpose information and is somewhat ambiguous.

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

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

For a simple one-parameter dashboard endpoint with no output schema, the description adequately explains what data will be returned. It could be more complete by naming sibling alternatives or clarifying the PRO/access-token relationship, but the essential calling information is present.

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

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

There is one optional parameter and schema description coverage is 100%, so the schema already explains that access_token is a subscriber token from /success or Authorization: Bearer. The description adds no additional parameter semantics, which is acceptable given full schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states that the tool returns all key indicators at once, including latest value, prior period, percent change, and CPI year-over-year inflation. That is a clear data-retrieval purpose, but it does not distinguish the tool from siblings indicator and vector_series.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit guidance on when to use dashboard versus indicator or vector_series. The phrase 'All key indicators at once' hints at a summary view, but the agent must infer that usage from contrast rather than from stated alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden and does disclose two real traits: there is no cost ("FREE") and the return is the last 3 periods plus percent change. It says nothing about failure behavior for an unrecognized name, whether values are seasonally adjusted by default, or units, which are the main behavioral unknowns for a data lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two terse sentences, front-loaded with the cost signal and the core purpose, with the valid values and return window packed in without waste. Nothing is redundant.

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

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

For a one-parameter, no-output-schema lookup, the description covers purpose, valid inputs, cost, and return shape — enough to call it correctly. Only units and error behavior are absent, which are minor for this tool's complexity.

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

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

Schema coverage is 0% and the single `name` parameter is an unconstrained string with no enum, so the description's enumeration of valid values (cpi, cpi_sa, unemployment_rate, employment, gdp, new_housing_price_index, population) is essential compensation. It still does not state case sensitivity or whether values outside the list are accepted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (latest value of a Canadian indicator) and enumerates exactly which indicators are covered, so an agent knows the domain of the tool. It does not name or contrast with siblings dashboard or vector_series, which likely offer related series data, so differentiation is left implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

"FREE" plus the short 3-period return window implies this is the lightweight choice for a quick snapshot, but the description never says when to prefer it over vector_series or dashboard, nor when not to use it. Usage must be inferred from the return-shape hint.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden, and it does disclose two real behaviors: a hard cap of 60 latest periods and that the series title is included in the response. However it says nothing about the PRO/subscription requirement that the access_token implies, error behavior for invalid vectors, or what happens when periods exceeds the cap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single compact sentence with the most decision-relevant facts front-loaded ('PRO.' then resource then example then limits). The fragmentary grammar and the unexplained 'PRO.' token cost it a point, but nothing is wasted.

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

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

For a 3-parameter tool with no annotations and no output schema, the description covers the essentials (what resource, example ID, period cap, title in response) but leaves the PRO/token requirement, error cases, and the shape of the returned data unaddressed. Adequate but with clear gaps.

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

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

Schema coverage is only 33% (just access_token), so the description must compensate and largely does: the example '41690973' clarifies the expected vector ID format, and 'up to 60 latest periods' explains the periods parameter's meaning and ceiling. The access_token semantics live in the schema, and the discrepancy between the '60' cap and the unlimited 'number' type is not addressed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource (Statistics Canada vector) and gives a concrete example ID (41690973), plus the scope of data returned (up to 60 latest periods and series title). The verb is only implied by the fragment structure, and it does not explicitly contrast itself with the indicator or dashboard siblings, but an agent can tell this is the per-vector data retrieval tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'PRO.' hints at a paid-tier prerequisite but is never explained, and there is no statement of when to choose vector_series over indicator or dashboard. No exclusions, no prerequisites about the access_token, no guidance on period limits beyond the reported 60 cap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.