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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false), lowering the bar. The description adds the meaningful trait that nothing is precomputed and the view evaluates live at read time, which is real context beyond annotations. It still omits creation side effects, duplicate-name/error behavior, and auth requirements, so it is minimum-viable rather than rich.

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?

It is front-loaded, leading with the verb+resource, then the filter mechanics, then the dynamic-read note. The middle field inventory ("keywords or keyword kinds, platforms, status, relevant, ...") is somewhat long and overlaps with the schema, but it functions as a useful at-a-glance overview and never buries the key sentences.

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?

This is a complex tool with a large nested filter object and no output schema, yet the description covers the filter's composition semantics and the dynamic evaluation model. The rich schema carries all field-level detail, so the description is complete enough for correct invocation; only return shape and error behavior are left implicit, which is acceptable without an output schema.

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, but the description goes beyond per-field docs by explaining how conditions combine: lists match any value, not-lists match none, all conditions are AND-joined, and anyOf adds OR groups where one must match. That composition logic is the genuinely hard part of the filter and is only partially conveyed by the nested schema, so it earns a bump.

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 states a specific verb and resource ("Saves a view") and names the two things needed (a name and a filter), so the core intent is unmistakable. It distinguishes itself from search_mentions by framing the filter as reusable, and the field list previews the resource's shape. It stops short of naming any sibling to contrast against (e.g., update_view, search_mentions), which keeps it at a 4.

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 is implied rather than stated: referencing search_mentions' fields signals this is the saved/persistent counterpart to an ad-hoc search, and "Nothing is stored ahead of time, so the view shows whatever matches when read" hints at when a view is appropriate. There is no explicit when-to-use/when-not or named alternative, so it lands at implied guidance.

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