macro_canada_new_house_rate

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 data source (East Money) and the return type (pandas.DataFrame), which are useful behavioral details beyond the annotations. It does not describe data granularity or date range, but for a zero-param read-only tool this is acceptable.

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 concise and well-structured, with the title, source URL, return label, and return type each on their own line. Every line provides useful information without verbosity, making it easy for an agent to parse.

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?

Given the tool's simplicity (zero parameters, read-only, clear annotations), the description provides sufficient context: it identifies the data source, the specific indicator, and the return type. While it could mention whether the data is historical or current, the URL and return type 'pandas.DataFrame' imply a tabular dataset, which is adequate.

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 an empty input schema, so the baseline for parameter semantics is 4. The description adds no parameter information, but none is needed. The schema coverage for parameters is effectively 100% since no parameters exist.

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: it retrieves Canada new housing starts data from East Money (东方财富) economic data. The title and return type (`:return: 新屋开工`, `:rtype: pandas.DataFrame`) specify the exact indicator and output format, distinguishing it from sibling macro_canada_* tools.

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 provides the data source (URL) and confirms it is a data retrieval operation, but does not explicitly state when to use this tool over alternatives. The usage is implied by the name and category, but no exclusions or alternative recommendations are given.

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