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

The description states it 'Returns the full series JSON (description + observations)', adding value beyond annotations which already declare readOnlyHint, idempotentHint, and non-destructive behavior. No contradictions.

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?

Three sentences that efficiently convey purpose, distinction, return type, and naming context. No unnecessary words; well structured.

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 single-parameter tool with no output schema, the description adequately explains what the tool returns (full series JSON) and how to use it. The naming note avoids confusion with other implementations.

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%, so the schema already describes the uri parameter. The description provides an example and mentions it's a www.ons.gov.uk URI, but this largely duplicates the schema's description. Minimal added semantic value.

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 the verb 'Fetch', the resource 'a single UK ONS time series', and the method 'by its www.ons.gov.uk URI'. It also contrasts with 'filterable datasets', distinguishing it from sibling tools like get_dataset.

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 explicitly distinguishes this tool from 'filterable datasets above', providing clear context for when to use this API. While it does not list all alternatives, the mention of 'get_series is used by many other packs' helps differentiate it from similarly named tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.