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

Beyond the readOnlyHint:false annotation, the description discloses many behavioral traits: real Python runs in a sandbox, returns a computed answer (nothing estimated by a model), refusal when no served series can answer, 10-40 second latency, series_limit error, and key_required error for missing API key. This is far richer than the annotation alone.

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 long but information-dense; every sentence provides useful details such as auth, latency, or error modes. It could be improved by using bullets or clearer section breaks, but the content is economical and avoids fluff.

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?

The description covers crucial operational aspects: authentication (API key, header, environment variable), latency, error types (series_limit, key_required, refusal), return contents, and cross-source joining. It is complete for a complex tool with no output schema, and the absence of an output schema is not a gap because the description names the returned artifacts.

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 75%, with start/end described as 'YYYY-MM-DD' and series described in the schema. The description adds value by explaining the series limit ('How many series one question may join is set by the caller's plan') and the resulting series_limit error, which is not in the schema. It does not explain start/end defaults, but the schema already provides format.

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 tool's purpose: 'ask a natural-language question about the served official statistics' and specifies what it returns (computed answer, Plotly chart, code, citations, verification badge). It distinguishes itself from siblings by positioning as 'the flagship' and highlighting cross-source joining, which other tools like get_observations or get_series do not offer.

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 conveys usage context by explaining when cross-source joins are relevant ('one question may join series from DIFFERENT agencies') and mentions the series limit based on the caller's plan. However, it does not explicitly name alternative tools or state when NOT to use this tool, relying on the sibling list to imply differentiation.

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