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

The description discloses the concrete return payload — model id, name, format, submitter, date — and the facet-count breakdown by curation status, modelling approach, and ontology cross-references. This goes well beyond the annotations' readOnly/openWorld/idempotent hints and provides an agent with an accurate expectation of the result shape.

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?

Four sentences, each with a distinct job: scope, epistemic authority, return shape, and accepted search terms. No filler, though the long enumerated examples make it denser than strictly necessary.

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 no output schema, the description supplies the essential return fields and facet categories an agent needs to interpret results. Combined with full parameter documentation and safety annotations, nothing critical is missing for invoking the tool 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 covers all 3 parameters at 100%, so the baseline applies. The description's query-type list mirrors the schema's query description and adds no new syntax, format, or boundary details beyond what is already in the input 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?

Opens with 'Search BioModels for published, executable mathematical models of biological systems', giving a specific verb, resource, and scope. It also clarifies this is the authoritative route for finding runnable published models versus web search's paper results, though it does not explicitly distinguish itself from the sibling biomodels_files or biomodels_model tools.

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?

Explicitly positions the tool as AUTHORITATIVE for determining whether a published computational model exists and is runnable, contrasting with web search. It lists acceptable query types, giving an agent a clear trigger condition for invocation. It doesn't state exclusions or when to prefer biomodels_files/model, so not a 5.

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