OpenWeather for agents

Get product

get_product

Read-onlyIdempotent

Returns one product by slug: its live catalogue entry (price, licence, lifecycle state, the specification address) together with the routes fetch_data can call and the parameters each route requires, taken from the platform's published product record. Needs no key and charges nothing. Use it before fetch_data — the route names come from here; an unknown slug answers with the slugs the catalogue serves.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "product": "<product>"
    },
    "name": "get_product"
  }
}

Input Schema

Name	Required	Description	Default
`product`	Yes	a product slug from list_products

Output Schema

Name	Required	Description	Default
`body`	No
`fault`	No
`usage`	No
`record`	No
`status`	No
`account`	No
`headers`	No
`upstream`	No
`body_text`	No
`configure`	No
`transport`	No
`key_source`	No
`request_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 6, 2026

TDQS

A4.5/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark the tool read-only, idempotent, and non-destructive. The description adds non-obvious context: no API key is needed, it charges nothing, data comes from the platform's published product record, and an unknown slug returns the catalogue's served slugs. There is no contradiction with the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, with the core return value front-loaded, followed by usage guidance and an edge case. Every clause adds value: content, routing, auth/cost, or error behavior. No fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read-only tool with an output schema and strong annotations, the description covers output content, its relationship to fetch_data, error behavior, and authentication/cost. Nothing an agent needs to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents the only parameter product at 100% coverage, including its pattern and source ('a product slug from list_products'). The description reinforces that the parameter is a slug and adds unknown-slug behavior, but it does not significantly extend the schema's parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Returns one product by slug' and enumerates the contained catalogue fields (price, licence, lifecycle state, specification address) plus route data for fetch_data. This clearly differentiates it from list_products and fetch_data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly instructs 'Use it before fetch_data' and explains that route names come from this tool. It also describes the unknown-slug fallback. It does not explicitly name list_products as an alternative, but the 'one product by slug' scope and the input schema's reference to list_products make the selection context clear.

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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