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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating a safe, side-effect-free operation. The description adds minimal behavioral context beyond stating it's an in-silico simulation. It does not mention constraints like the maxPeptides cap or the handling of non-AA characters, which are in the schema but not in the description.

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, front-loaded sentence that conveys the essential information without any verbose or redundant phrasing. Every word contributes to understanding the tool's core function and output.

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 an output schema, the description only partially describes the return values (position, length, neutral mass). It does not specify whether the output is a list, the ordering, or how missed cleavages or other parameters affect results. A more complete description would clarify the output structure.

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% coverage with parameter descriptions, so the description does not need to repeat them. However, the description adds no extra meaning beyond the schema, such as usage tips or parameter relationships. It meets the baseline for a well-documented schema.

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 action ('cleave a protein') and the output ('report each peptide's position, length and neutral mass'). It uses specific verb+resource and distinguishes from sibling tools like 'protein_properties' or 'characterize_sequence' which have broader or different purposes.

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 implies usage for in-silico digestion but provides no explicit guidance on when to use this tool vs. alternatives, nor does it mention prerequisites or exclusions. The context is clear but lacks direct when-to-use and when-not-to-use instructions.

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