get_trial_details

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it clearly describes what information will be returned, it doesn't address important behavioral aspects: whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or response format. The description states what data is included but not how the tool behaves operationally.

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 efficiently structured as a single sentence that clearly states the purpose and enumerates the specific data fields included. It's appropriately sized for a tool with one parameter and no annotations. While it could be slightly more concise by removing some redundancy in the field list, every element serves a purpose in clarifying what information will be returned.

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 moderate complexity (retrieving detailed clinical trial information), lack of annotations, and absence of an output schema, the description is minimally adequate. It clearly states what information will be returned but doesn't address behavioral aspects, usage context, or response structure. For a data retrieval tool with no output schema, more detail about the return format would be helpful, but the description covers the essential purpose.

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 input schema has 100% description coverage, with the single parameter 'nctId' well-documented as 'NCT编号，例如：NCT04852770'. The description doesn't add any parameter information beyond what's in the schema - it doesn't explain the NCT ID format further or provide additional context about parameter usage. With complete schema coverage, the baseline score of 3 is appropriate.

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: '获取指定临床试验的详细信息' (get detailed information for a specified clinical trial). It specifies the verb ('获取' - get) and resource ('临床试验的详细信息' - clinical trial details), and lists specific data fields included (PI researcher info, hospital locations, contact info, study description, criteria, outcome measures). However, it doesn't explicitly distinguish this from sibling tools like 'search_clinical_trials' or 'search_by_location' which likely return different types of results.

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 no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tools at all, nor does it explain that this tool retrieves detailed information for a specific trial (using NCT ID) while the search tools likely return lists of trials based on criteria. There's no context about prerequisites, limitations, or appropriate use cases.

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