get_london_weather
[COST: ] Get current weather in London
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
[COST: ] Get current weather in London
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. 'Get current weather' clearly implies a read-only operation and scopes it to current conditions, but it does not disclose any additional behavioral traits such as external API usage, rate limits, or absence of side effects. For a simple retrieval tool this is adequate but lacks explicit behavioral context.
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 core sentence is short and front-loaded: 'Get current weather in London.' However, the ' [COST: ]' prefix is empty and adds noise without providing any useful information, preventing a perfect score.
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 zero-parameter, read-only weather tool with an output schema available, the description is largely sufficient. It states what is returned (current weather) and where (London). The main gap is the absence of explicit sibling guidance or any note about alternate city tools, but the simple scope means the description does not leave major ambiguity.
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 tool has zero parameters, so the parameter semantics are inherently clear. The description adds the hardcoded scope ('London'), and since no input is needed, there is no parameter ambiguity to resolve. This matches the baseline for a 0-parameter tool.
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 a specific action ('Get'), a specific resource ('current weather'), and a specific location ('in London'). This clearly distinguishes it from sibling tools like get_berlin_weather or get_nyc_weather based on the city.
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 implies this tool should be used when current London weather is requested, but it provides no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives such as get_berlin_weather or get_paris_weather for other cities, so routing among the many weather siblings is left to inference.
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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