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

Annotations already declare the tool as read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds the 'in one call' batching behavior and an example group, but does not disclose output format or pagination. This is adequate but not rich.

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 three concise sentences: main purpose, useful group example, and parameter mode. It is front-loaded with the primary function, and every sentence adds value without padding.

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 4-parameter read-only tool with rich annotations and no output schema, the description provides core purpose, a concrete example, and parameter selection guidance. It lacks explicit return-format details, but the purpose implies observations, making it sufficient for invocation.

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?

The schema covers 100% of parameters, so the baseline is 3. The description adds a hint about choosing between recent and date-window modes and provides a useful group value, but this only slightly extends the schema's descriptions.

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 returns observations for every series in a named group in one call. This distinguishes it from per-series observation tools and the concrete example 'FX_RATES_DAILY' reinforces the scope.

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 clear context: use this when you need observations for all series in a group. It also gives a useful group example and parameter guidance ('Use recent=N or a start_date/end_date window'). However, it does not explicitly name alternatives like get_observations for single-series queries.

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