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

Annotations declare readOnlyHint=false, idempotentHint=false, and destructiveHint=false, which is an unusual combination for what appears to be a metadata-read tool. The description does not reconcile this apparent contradiction or explain why a 'describe' operation would not be read-only. With annotations covering some behavioral traits but in a way that conflicts with the tool's apparent purpose, the description needed to clarify the write-like or stateful behavior, and it does not.

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 two sentences, front-loaded with the resource and the content returned, followed by a sequencing instruction. Every phrase earns its place with no filler.

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?

An output schema exists, so the description need not explain return values, and it correctly summarizes the key returned content. However, for a two-required-parameter tool with 0% parameter coverage and anomalous annotations (readOnlyHint=false on a describe operation), the description leaves important gaps about what 'schema' means and why the tool is not read-only.

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 description coverage is 0%, so the two required parameters ('schema' and 'dataset_code') are completely undocumented in both the schema and the description. The description implies the tool operates on 'one dataset' but never explains what 'schema' means (e.g., database schema or dataset schema namespace) or how to obtain valid values. The description must compensate for the coverage gap and fails to do so.

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 verb (describe) and resource (one dataset) and lists the content returned (topic, methodology, discontinuities, base-change notice, live dimensions, example series). It does not explicitly differentiate itself from siblings like get_series or search_datasets beyond the implicit reference in the call-order instruction, so it is clear but lacks full sibling differentiation.

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?

It provides explicit sequencing guidance: 'Call after search_datasets narrows you to a dataset.' This tells the agent when to use the tool in relation to one sibling. However, it does not state when NOT to use it or name alternatives for retrieving series-level data (e.g., get_series), leaving some conditions implicit.

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