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

Annotations already carry the safety profile (readOnlyHint=true, openWorldHint=true, destructiveHint=false), so the description's 'non-consequential' claim is aligned but not additive on safety. It adds genuine behavioral disclosure beyond annotations: 'Fify will perform a bounded trusted Wikimedia portrait lookup' for named real-person profiles, plus the trust boundary of never inventing media URLs. No contradiction with annotations.

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?

Five dense sentences, roughly 110 words, with the core purpose front-loaded and workflow/constraints following in logical order. Every sentence earns its place: trigger condition, reasoning sequence, immediate-invocation rule, profileSubject procedure, media constraint. No filler or redundancy.

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?

An output schema exists, so return-value documentation is unnecessary. The description, schema, and annotations together cover the invocation trigger, grounding workflow, profile-image behavior, and media provenance constraints. Minor gaps remain around the role of continuationState and originalRequest, but these are inferable from their names and the sibling read tool.

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 description coverage is only 10%, so the description must compensate. It does add real parameter guidance for profileSubject (set to canonical name unless no image requested), media (pre-resolved Wikimedia/Openverse only, never guess URLs), and groundedAnswer (always pass the authoritative plain answer). However, required params like originalRequest, continuationState, and suggestedRefinements receive no semantic enrichment, leaving part of the burden unmet.

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 opens with a specific verb+resource+condition: 'Render a fully grounded answer as a non-consequential interactive information view when structure or interaction materially improves it.' This names the deliverable (interactive view), the input (grounded answer), and the trigger condition, and it is clearly distinguished from the sibling read_information_ui_run by the render-vs-read contrast.

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 context is explicit and actionable: invoke 'when structure or interaction materially improves it', complete factual reasoning first, always pass the authoritative plain answer, avoid extra retrieval when sufficient facts are supplied, and never guess media URLs. It tells the agent not just what to do but the order in which to do it.

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