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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context by listing well-known series identifiers and the choice between recent observations or date-range windows. It also implicitly communicates the mutual exclusivity of the two modes, supplementing the annotation coverage.

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 sentences, front-loads the core purpose, then immediately gives concrete examples and parameter options. Every sentence earns its place, and there is no redundant or vague wording. This is a model of concise structure.

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 simple list-like tool with 4 parameters and no output schema, the description covers the core purpose, gives concrete series examples, and outlines both usage modes. It could mention the return format or error handling, but the tool is straightforward and the schema fills remaining parameter details, making this sufficient.

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 baseline is 3. The description reinforces comma-separated series names and provides practical examples, but it does not add new semantic meaning beyond what the schema already documents, such as precedence rules or date formats. The examples are helpful but not essential.

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 retrieves time-series observations for Bank of Canada series, with specific examples (FXUSDCAD, V39079). This goes beyond the generic name and distinguishes it from list_series or series_info, which cover metadata rather than observations.

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 explains the two primary usage modes (recent=N vs start_date/end_date) and clarifies that series names must be comma-separated. However, it does not explicitly contrast with sibling tools like get_group_observations or list_series, so the when-to-use guidance is only implied rather than explicit.

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