active_typhoons
FREE. Active tropical cyclones tracked by JMA (target list).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
FREE. Active tropical cyclones tracked by JMA (target list).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully discloses that the data is FREE and sourced from JMA, but says nothing about update cadence, geographic scope, or result format — the things that matter for a live-weather feed.
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 fragments with the most decision-relevant fact (FREE) front-loaded. No filler, though '(target list)' is opaque enough to not quite earn its place.
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 no-param read tool this is close to sufficient, but there is no output schema, so the description is the only place to say what a storm record looks like or how fresh the data is — and it doesn't.
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?
Zero parameters, so the schema baseline is 4. There is nothing for the description to clarify parameter-wise, and it correctly signals the tool takes no 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?
The phrase 'Active tropical cyclones tracked by JMA' names a specific resource and data source, so an agent knows what it gets back. The verb is implicit ('list') and '(target list)' is cryptic, and nothing distinguishes it from the sibling storm_list.
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 never says when to use this tool versus storm_list or storm_detail. There are no exclusions, prerequisites, or routing cues — an agent must guess whether this is the discovery endpoint or filtered by something.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.