get_dynamic_data

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

No annotations are provided, so the description carries the burden. It adds context about requiring a specific var_id and lists common variables, but it does not disclose output format, error handling, or read-only nature explicitly. Some transparency is present but not comprehensive.

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 well-structured with a clear purpose, requirement, usage guidance, and a list of common variables. While slightly long, every section contributes useful information, and the bulleted list improves readability.

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?

Despite lacking an output schema and annotations, the description provides adequate context with usage instructions, examples, and links to discovery tools. It covers the main use case well, though it does not explain return values or all parameters in depth.

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?

Since schema coverage is 100%, baseline is 3. The description adds value by providing concrete examples for var (e.g., 1452 = Population) and clarifying domain='0000' for national data, which enhances parameter understanding beyond the schema 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's function: 'Fetch data from BPS dynamic tables.' It specifies the requirement of a known variable ID and distinguishes itself from related tools like find_data and find_variable by explaining when each should be used.

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?

Explicit guidance is provided: 'Use find_data first for automatic search. Use this tool only if you already know the var_id' and 'Use find_variable to search for other variable IDs.' This clearly indicates when to use this tool versus alternatives.

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