ct_get_study

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. It mentions 'AI analysis,' which hints at additional processing beyond basic data retrieval, but does not specify what this entails—e.g., whether it's real-time, cached, or involves specific algorithms. It also omits details like rate limits, authentication needs, or error handling, leaving significant gaps in understanding the tool's behavior.

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 a single, efficient sentence: 'Get detailed study information by NCT ID with AI analysis.' It is front-loaded with the core purpose and includes a key feature ('AI analysis') without unnecessary words. Every part of the sentence contributes to understanding the tool's function.

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 lack of annotations and output schema, the description is incomplete. It does not explain what 'detailed study information' includes or what the 'AI analysis' produces, leaving the agent uncertain about the return values. For a tool with no structured output documentation, the description should provide more context on expected results and behavioral traits.

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 'nctId' parameter well-documented in the schema itself (including pattern and example). The description adds minimal value beyond this, only reiterating 'by NCT ID' without providing additional context like what the AI analysis does with the ID or any constraints. This meets the baseline of 3 since the schema handles the heavy lifting.

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: 'Get detailed study information by NCT ID with AI analysis.' It specifies the verb ('Get'), resource ('detailed study information'), and key identifier ('NCT ID'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'research_clinical_details' or 'ct_search_trials,' which might offer similar or overlapping functionality, preventing a score of 5.

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 mentions 'AI analysis' but does not explain how this differs from other tools, such as whether it's for specific types of studies or when other tools might be more appropriate. This lack of context leaves the agent without clear usage instructions.

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