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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false). The description adds meaningful behavior beyond them: the output is a heuristic hydrophobicity-based prediction rather than a trained topology model, which tells the agent how much to trust the classification. It does not, however, discuss limitations like window/angle sensitivity or overlap handling.

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?

Two sentences, both front-loaded with the highest-value information: what is computed and what is returned, followed by the reliability caveat. No filler or restatement of the name.

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?

With an output schema present, the description need not explain return values, and annotations carry the safety profile. What remains for the description — method, output granularity (per-window + spans), and the heuristic caveat — is all present, so an agent has enough to call it correctly.

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 window, angle, minWindows, protein, _subject and _files are all documented in the schema itself. The description adds only light framing ('per-window', 'windows collapsed into residue spans') that contextualizes window/minWindows without adding syntax or limits. Baseline 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?

Names a specific method (Eisenberg hydrophobic-moment plot) and a concrete output shape: per-window mean hydrophobicity and moment, class labels, and collapsed residue spans. It also implicitly distinguishes itself from trained topology predictors ('NOT a trained topology model'), though it never names the sibling (e.g. protein_topology) directly.

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 disclaimer 'NOT a trained topology model' implies when to prefer a trained predictor instead, but there is no explicit when-to-use/when-not statement and no named alternative. Usage is left for the agent to infer from the caveat.

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