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

Goes far beyond the readOnlyHint/idempotentHint annotations by defining the match_quality taxonomy (exact-label, exact-synonym, broader/narrower, fuzzy), guaranteeing no bare empty results on no-match, and describing returned xrefs and expand behavior. Rich, decision-relevant behavioral context.

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?

Dense and front-loaded: purpose and examples come first, followed by the match_quality taxonomy and no-match behavior. The match_quality list is long but earns its place because it drives user trust; a slightly tighter structure would be possible.

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 no output schema, the description carries the full burden of explaining return values — and it does: match_quality semantics, no-match fallback, xrefs, and expand. Nothing an agent needs to call or interpret results is left to guesswork.

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. The description adds practical meaning beyond the schema by explaining the effect of expand (descendant MONDO ids for subtype-inclusive filters) and by providing realistic example condition strings that clarify what counts as free-text input.

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 ('Resolve') and resource (Mondo Disease Ontology), and sharply differentiates itself from generic resolution tools by targeting condition/disease strings. Concrete use cases (clinical trial registry conditions, drug label Indications wording) make its niche unmistakable.

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?

Gives clear contexts for use: clinical trial registry conditions field, drug label wording, and subtype-inclusive filters via expand. However, it doesn't explicitly name sibling resolve_entity as an alternative or state when not to use this tool.

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