x402-weather
Weather: Weather forecast for a location.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | Lat to process | |
| lon | No | Lon to process | |
| city | No | City to process | |
| location | No | Location to process |
Weather: Weather forecast for a location.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | Lat to process | |
| lon | No | Lon to process | |
| city | No | City to process | |
| location | No | Location to process |
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, but it merely restates the core operation. It does not disclose the response format, units, data source, timezone handling, or any side effects or limitations.
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 with no filler words, and the core concept is front-loaded. However, the brevity comes at the cost of missing usage detail.
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 tool with 4 optional parameters and no output schema, the description omits essential context: how the agent should specify a location, what the forecast response will contain, and what happens if multiple or no parameters are supplied.
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 100%, giving a baseline of 3. The description's 'for a location' aligns conceptually with the four location-related parameters, but it adds no practical guidance on how to choose between lat/lon, city, or location, nor on format requirements.
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 identifies the resource clearly ('weather forecast') and the scope ('for a location'). It distinguishes this tool from the vast sibling list, where no other tool is weather-specific, though it lacks an explicit action verb like 'retrieve' or 'get'.
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 phrase 'for a location' implies the tool should be used when a weather forecast is needed, but it gives no explicit when-to-use or when-not-to-use guidance. It also doesn't clarify whether location means lat/lon, city, or a free-form location string, or which parameter should take precedence.
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.
The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.
Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.
1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.
The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.