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

Annotations already establish a safe, idempotent read, so the bar is lower. The description adds real value beyond them: the shape of each result (type, image, link, and a `context` field on screens) and that include_images is off by default with a recommended search-first workflow.

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?

Front-loaded with purpose, then query tactics, then result structure. It is somewhat long, but the final sentence on iterating searches earns its place as actionable guidance rather than 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?

An output schema exists, so return values needn't be spelled out; the description nevertheless summarizes them usefully. Combined with annotations, it covers what an agent needs to call the tool correctly, though the relationship to find_ui_materials is left unstated.

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 goes beyond the schema by prescribing query phrasing (short, facet-combining queries) and explaining the deferred-image workflow, which adds practical meaning over the parameter's terse definition.

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 (search) and the concrete resources: real iOS app screens, ordered user journeys, and website references, with examples ('Deleting account', 'paywall'). It names get_journey as a follow-up path but does not differentiate itself from the sibling find_ui_materials, which likely overlaps in scope.

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 query-style guidance: use short queries, combine facets, and 'search a few times with different words rather than one long sentence.' It also signals when to reach for get_journey for close inspection. Missing explicit exclusion of when NOT to use it versus find_ui_materials.

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