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

Beyond the readOnly/idempotent annotations, the description discloses the truncation limits (largest 8 outcome groups, or 5 for 4-5 peptides; 2 top findings, or 1 for 4-5 peptides), the no-ranking policy, the evidence-class taxonomy, and an important null-semantics caveat that a 0 human count does not mean no human study exists. That is real behavioral context the annotations cannot carry; it stops short of covering error behavior for unresolvable peptide names.

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 critical scoping and alternative-tool sentences are front-loaded, and the caveats each earn their place. The two parallel 'Each MCP column includes...' sentences are slightly repetitive and the phrase 'MCP column' is unexplained jargon, but there is no filler.

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 2-parameter, capped-comparison tool with an output schema and full annotation coverage, the description supplies everything an agent needs: scope, limits, interpretation caveats, and alternative routing. Return-value explanation is a bonus rather than a requirement given the output schema exists.

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 the baseline is 3, and the description does add meaning by tying peptide count to output caps. However, the 'view' enum (compact/full) is never mentioned in the description, leaving its effect on result detail undocumented outside the terse enum description 'Default compact.'

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 opening sentence names a specific verb (return) and enumerates the exact payload: identity, evidence counts, outcome groups, top findings, plus shared outcome groups for 2-5 peptides. It also explicitly distinguishes itself from get_peptide_brief, so an agent can tell the batch-comparison tool apart from the single-peptide tool without opening either schema.

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?

It gives a positive trigger ('Use this for a comparison in one call') and three named alternatives with their selecting conditions: get_peptide_brief for one peptide, get_evidence_map for all outcome groups, search_findings for more findings. Routing is fully determined by the description.

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