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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing that results are ranked and that `saude`-tagged health data is filtered out unless the user opted into AI sharing in settings, a privacy constraint not visible anywhere else. It does not describe result volume/pagination behavior.

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?

Three compact sentences with the core purpose front-loaded; no filler. The health-data sentence is longer but carries non-obvious behavioral information, so it earns its place rather than padding the text.

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 an output schema present, return values need not be explained, and the description covers purpose, invocation context, and a privacy caveat. The one meaningful omission is routing guidance against the overlapping recall/fetch siblings, which matters for a search-style tool in this toolset.

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 50%: `query` is documented in the schema while `limit` has only a default and min/max bounds. The description adds nothing about either parameter (no guidance on query phrasing or when to raise limit), so it neither compensates for the coverage gap nor extends the documented field. Baseline 3 is appropriate.

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 and resource ('Search the user's CortexPlus memory') and the return shape ('ranked matches'), which is more than a restatement of the name. However, it never distinguishes itself from plausible siblings such as recall, fetch, or memory, so an agent cannot tell them apart from the text alone.

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?

'Use this to find what the user has stored before answering from memory' gives a clear triggering context, which is genuinely helpful. It stops short of the 5 level: no when-not conditions and no named alternatives among the overlapping siblings (recall, fetch, context_packs).

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