macro_canada_cpi_yearly

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds the source URL and return type (pandas.DataFrame), providing some extra context but no additional behavioral details such as data range or update frequency.

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 compact and free of fluff, containing the data source, return type, and a brief descriptor. The line breaks are slightly awkward but do not detract from its efficiency.

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 zero-parameter, read-only tool with no output schema, the description adequately identifies the data (Canada yearly CPI) and return format (DataFrame). It lacks details on the exact data columns or time range, but such details are less critical for a simple data fetch.

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 tool has zero parameters, and the schema coverage is 100% with an empty schema. The description correctly notes the return type and data source, which is sufficient given no parameters require explanation.

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 identifies the tool as fetching Canada's yearly Consumer Price Index (CPI) rate from Eastmoney. It is specific to the yearly CPI metric, distinguishing it from siblings like macro_canada_cpi_monthly and macro_canada_core_cpi_yearly.

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?

No guidance is provided on when to use this tool versus alternatives (e.g., monthly CPI or core CPI). It simply names the data source and return type without contextual use cases or exclusions.

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