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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered; the description adds genuinely new behavioral context by disclosing computational provenance (validated against pyteomics, cross-checked against OpenMS) and the fidelity model (charge states up to a maximum, neutral-loss and radical variants). It does not discuss limits such as peptide length caps or performance, keeping it short of a 5.

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?

A single front-loaded sentence that names the output before qualifying it, with the provenance check kept in a trailing parenthetical. Dense but every clause carries information; no filler or restatement of the tool 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?

For a 5-parameter tool with a nested _subject/_files project reference and an output schema (so return values need no explanation), the description adequately covers what is computed and with what chemical fidelity. It leaves unstated how the _subject/_files record arguments interact with the required sequence, which is the main residual gap.

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 coverage is 100%, so baseline would be 3. The description nonetheless adds semantic meaning beyond the enum list: it explains that a/b/c derive from the N-terminus and x/y/z from the C-terminus, and that ionTypes can include neutral-loss and radical variants, and it restates that maxCharge means every charge from 1 up to the maximum.

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?

States a specific verb-and-resource: generates the theoretical MS/MS fragment ion ladder of a peptide, and enumerates the series (a, b, c from N-terminus; x, y, z from C-terminus) plus neutral-loss/radical variants. An agent can tell this is a prediction tool rather than a spectral reader, but no sibling (e.g. peptide_mass, score_spectrum, read_mgf) is named to sharpen the boundary.

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?

Usage is only implied: this produces theoretical fragment ladders, which one infers is for spectral interpretation or matching against score_spectrum/read_mgf. There is no explicit 'use this when...' or 'use peptide_mass instead for...' guidance, and no stated prerequisites despite the description's detail elsewhere.

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