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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds value by disclosing the ranking strategy and the returned fields (id, title, type, snippet), but says nothing about scoring behavior, empty-result handling, or cross-brain scope.

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?

A single, tightly packed sentence with no filler, and the core action and retrieval method are front-loaded before the return fields. Every clause earns its place.

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 present, the description shoulders the return-value burden and does so adequately by naming the four returned fields. Combined with 100% schema coverage for inputs, an agent has enough to call it, though ordering and scope semantics remain implicit.

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 100%, so every parameter (query, type, brain, limit) is already documented in the schema, including defaults and constraints. The description adds no syntax, format, or matching-semantics detail beyond that, so the baseline of 3 applies.

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 gives a specific verb (search) and resource (memories), plus the retrieval method (semantic + keyword) and the fields returned. It distinguishes itself from memory_list by implying ranked relevance, but it never names or contrasts against plausible siblings like memory_list or recall, so an agent must infer the boundary.

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 only implied: 'search over memories' tells the agent this retrieves matches, but there is no explicit when-to-use, when-not-to-use, or routing to alternatives such as memory_list or recall. The agent must infer selection from the name alone.

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