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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds that results are ranked 'best matches,' but says nothing about paging behavior, result caps, or empty-result handling beyond what the schema notes. Useful but thin against an already-rich annotation set.

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?

Two sentences with zero filler: the capability first, the usage trigger second. Front-loaded and appropriately sized for the tool's complexity.

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 and the next_offset field need no prose. Combined with 100% parameter coverage and explicit annotations, the description supplies the one thing structured data cannot: when to reach for this 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 100%, so every parameter (tags, tier, limit, offset, source, event_type, date bounds) is already documented, including the next_offset paging convention. The description only implies that query is natural language and adds nothing beyond the schema, so the baseline 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?

States a specific verb (search) and resource (user's stored memory) and the outcome (best matches), which separates it from get_memory and list_memories by implying relevance ranking rather than lookup or enumeration. It never names those siblings explicitly, so differentiation is inferable rather than stated.

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 a clear usage trigger: 'Use this before answering anything that depends on what the user told you previously.' That is actionable context, but there are no exclusions and no named alternatives (e.g., get_memory for an exact known ID, list_memories for full enumeration), which leaves routing to the agent.

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