Canada Weather Forecast MCP

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 add real context: the call is free and results are resolved to the city nearest the postal code rather than the exact location. It omits failure behavior for invalid or unmatched postal codes and any caching/rate-limit notes.

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?

One sentence plus a pricing flag, front-loaded with the cost differentiator and then the scope. No filler.

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 read tool with no output schema, the description covers what is returned, the source, and the geocoding behavior. Only edge-case behavior (invalid postal code) is left unstated.

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?

The single parameter has 0% schema description coverage, but the description explains its semantics — it is a postal code used to find the nearest city, implying approximate rather than exact geolocation. It doesn't state accepted formats or country assumptions, which matters for a postal-code input.

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 concrete resource (current conditions plus the next 3 forecast periods), the data source (Environment Canada), and the geographic resolution (city nearest a postal code). The explicit 'next 3 forecast periods' scope implicitly separates it from forecast_full, though no sibling is named.

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?

There is no statement of when to use this versus forecast_full or sites_forecast, nor any prerequisite or exclusion. The limited 3-period scope hints at the tradeoff but the agent must infer it.

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?

No annotations are provided, so the description carries the full behavioral burden. It lists what data is returned but does not state that the operation is read-only, mention rate limits or data freshness, or explain the authentication requirement beyond the bare "PRO" label and the schema's access_token description.

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 tight sentence with no wasted words, and the returned components are front-loaded. The leading "PRO." is terse and not fully self-explanatory but does signal subscription access.

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?

Because there is no output schema, the list of returned elements (7-day, hourly, normals, warnings, sunrise/sunset) is useful. However, it omits sibling differentiation and postal-code format expectations, which are important given the two competing forecast tools.

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 50%, so the description should compensate for the undocumented `postal_code` parameter. It says the forecast is "for a postal code," which identifies the input but does not clarify the expected format or country context; `access_token` is already documented in the schema.

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 (forecast) and enumerates its components (7-day, hourly, normals, warnings, sunrise/sunset) scoped to a postal code. The word "Full" hints that it is broader than the sibling `forecast`, but it never explicitly contrasts the two.

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?

Gives no guidance on when to use this tool instead of `forecast` or `sites_forecast`. "PRO" implies a subscriber-only feature but does not explain the selection conditions or prerequisites beyond what the schema shows.

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?

No annotations are supplied, so the description carries the full burden. It does disclose two real behavioral traits — a PRO subscription requirement and a hard 25 postcode limit — but says nothing about what happens when the limit is exceeded, error behavior, or rate limits.

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 short sentences with no filler, and the tier flag is front-loaded before the functional statement. Nothing could be removed without losing meaning.

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?

Given no output schema, no annotations and only 2 parameters, the description covers the essentials: what is returned (current conditions, today's forecast), the input domain (postal codes) and the batch ceiling. Details like units, returned fields, and geographic coverage remain unstated but are minor for a simple read tool.

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 50%: access_token is documented in the schema but postal_codes is bare. The description contributes the important 25-item maximum for the array, yet leaves the postal code format and country/region coverage entirely unspecified.

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 verb-and-resource: returns current conditions plus today's forecast for a bounded set of postal codes. The postal-code scope and the 25-item cap implicitly separate it from the sibling tools forecast and forecast_full, though neither sibling is named.

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 'PRO' marker signals a paid-tier prerequisite and the 25 postal code cap implies batch use, so the intended context is inferable. However there is no explicit when-to-use framing and no statement of when an agent should prefer forecast or forecast_full instead.

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