get_schema

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's purpose and usage context but lacks details on permissions, rate limits, error handling, or response format. The description doesn't contradict any annotations, but it misses key behavioral traits for a tool that likely involves data access.

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 two sentences, front-loaded with the core purpose and followed by a practical usage guideline. Every sentence adds value without redundancy, making it efficiently structured and appropriately sized for a simple tool.

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 low complexity (one parameter, no nested objects) and high schema coverage, the description is mostly complete for its purpose. However, with no output schema and no annotations, it could benefit from mentioning the response format or any constraints, slightly limiting completeness for an agent invoking the tool.

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 description coverage is 100%, with the input schema fully documenting the dataset_id parameter's type, format, and pattern. The description adds no additional parameter semantics beyond what the schema provides, such as examples or edge cases, so it meets the baseline score of 3 for high schema coverage.

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 specific action ('Get the schema') and resource ('for a specific dataset'), with the explicit purpose of learning field names before writing queries. It distinguishes from siblings like list_datasf, query_datasf, and search_datasf by focusing on metadata retrieval rather than data listing, querying, or searching.

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 explicitly states when to use this tool ('Call this before writing queries to learn the correct field names'), providing clear context for its application. It implies an alternative workflow where users might skip this step and risk errors, though it doesn't name specific sibling alternatives for schema-related tasks.

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