predict_admet_properties

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 states the tool predicts ADMET properties but lacks details on how predictions are made (e.g., model used, accuracy), what the output format is, or any limitations (e.g., rate limits, data requirements). For a prediction tool with zero annotation coverage, this is a significant gap in transparency.

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 that directly states the tool's purpose without unnecessary words. It is front-loaded with the key information (predicting ADMET properties) and avoids redundancy, making it highly concise and well-structured for quick understanding.

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 complexity of predicting ADMET properties, no annotations, and no output schema, the description is incomplete. It does not cover behavioral aspects like prediction methods, output format, or limitations, which are crucial for a tool of this nature. The description alone is insufficient for an agent to use the tool effectively without additional context.

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%, so the schema already documents both parameters (cid and smiles) with clear descriptions. The description does not add any meaning beyond this, such as explaining the relationship between cid and smiles or usage examples. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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: predicting ADMET properties (Absorption, Distribution, Metabolism, Excretion, Toxicity). It specifies the verb 'predict' and the resource 'ADMET properties', making it distinct from siblings like 'assess_drug_likeness' or 'get_toxicity_info' which focus on different aspects. However, it doesn't explicitly differentiate from all similar tools, such as 'assess_drug_likeness' which might overlap in scope.

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 does not mention prerequisites, context, or exclusions, such as how it differs from 'assess_drug_likeness' or 'get_toxicity_info'. Without this, users must infer usage from the tool name alone, which is insufficient for effective tool selection.

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