macro_canada_unemployment_rate

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and side-effect behavior. The description adds a source URL and return type (pandas DataFrame) but does not disclose additional behavioral traits such as data frequency, historical range, or units. This modest addition warrants a middle score.

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 extremely short, consisting of a title, URL, and return type. While every line is purposeful, it is more of a docstring fragment than a structured description. It is concise and front-loaded with the resource name, but lacks a clear narrative sentence.

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 no-parameter read-only tool, the description provides the source and return type. However, it omits practical details like the time series frequency (e.g., monthly), the historical period covered, or column names. Since there is no output schema, these details would help the agent set expectations. The annotations compensate somewhat, but the description remains minimal.

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 input schema is empty with 100% coverage. According to the rubric, a baseline of 4 is appropriate when there are no parameters. The description does not need to explain parameter semantics, and no information is missing.

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 resource: Eastmoney economic data for Canada's unemployment rate. It also specifies the return type (pandas DataFrame) and provides a source URL. However, it lacks an explicit action verb like 'get' or 'retrieve', relying on the tool name and context, which slightly weakens clarity.

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 gives no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or distinguish it from other macro economic data tools for Canada or other countries. An agent is left without context on selection.

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