Retrieve past weather for any city on a specific date, at least five days back. Enter city name and date to get historical conditions.
Look up past weather for a city on a specific date.
Args: city: Name of the city, e.g. "Toronto" date: The date in YYYY-MM-DD format. Must be at least 5 days in the past.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | ||
| date | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the purpose and a date constraint but does not mention side effects, error handling, expected return behavior, or any operational details. The agent is left blind about what happens with invalid dates or what the response structure contains beyond the output schema.
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 extremely concise, using two sentences to state the purpose and parameter details. The purpose is front-loaded, and every sentence adds value without redundancy. It is well-structured for quick parsing by an agent.
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 two-parameter lookup tool with an output schema, the description covers the essential facts: what it does, the required parameters, and an important validation rule. The output schema handles return values, so the description is sufficiently complete for calling the tool correctly. Minor gaps like error messages or rate limits are not critical given the tool's simplicity.
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 description coverage is 0%, so the description must compensate. It does: 'city' is explained with an example, and 'date' is given a specific format (YYYY-MM-DD) and a critical constraint (at least 5 days past). This adds meaningful semantic information beyond the plain string type 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?
The description clearly states a specific verb ('look up') and resource ('past weather') for a city on a specific date. The word 'past' distinguishes it from sibling tools for current and forecast weather, so an agent can easily tell this is for historical data.
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 clear context that the tool is for past weather and includes a specific constraint (date must be at least 5 days in the past). However, it does not explicitly name alternative tools or state when not to use it, leaving implicit that current and forecast tools are for other timeframes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.