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

With no annotations, the description carries the full behavioral burden. It usefully discloses the computed outputs (DAR, aggregation risk, payload properties), which lets an agent predict behavior, but it omits the fact that an api_key is required, whether the computation is deterministic, and any limitations or cost considerations for a multi-property estimation.

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?

Front-loaded with purpose, then a clean parameter list and return summary; every line earns its place. Slightly redundant since the 'Returns' block restates outputs already implied by the opening sentence, but it remains compact and scannable.

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 an output schema exists, return-value explanation is not strictly required, yet the description helpfully summarizes them. Purpose, inputs, and outputs are all covered; the only gaps are the missing usage guidance and the undocumented api_key, which keep it short of complete.

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 0%, so the description must compensate, and it documents 3 of 4 parameters with real meaning: antibody amino acid sequence, payload SMILES including concrete examples (MMAE, DM1), and target DAR. Only the api_key parameter is left unexplained, and sequence/SMILES format constraints are not specified.

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 names a specific verb ('Design an antibody-drug conjugate') and enumerates exactly what is estimated: DAR, total molecular weight, conjugatable cysteine/lysine sites, aggregation risk, and payload hydrophobicity. It is clearly distinguishable from generic siblings like covabio_antibody or covabio_developability, though it never explicitly names a sibling to route against.

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?

There is no statement of when to use this tool versus alternatives (e.g. covabio_antibody for plain sequence analysis, or covabio_developability for general developability). The ADC-specific framing implies its niche, but no exclusions, prerequisites, or alternative-selection guidance is given.

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