recall

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

No annotations are provided, so the description carries the full burden. It discloses that it performs a semantic search and returns top-N items, which implies a non-destructive read operation. However, it does not explicitly state that it is read-only, describe behavior when no memories match, or mention any auth or rate-limit considerations. The query-style guidance adds useful context but more behavioral disclosure would be needed for a higher score.

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?

The description is compact, consisting of four short sentences that each deliver distinct value: what the tool does, the result format, when to use it, and query guidance. There is no filler or repetition, and the embedded example is illustrative without adding bulk. This is a model of efficient writing.

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?

Given the full schema coverage and the presence of an output schema, the description needn't explain return values. It provides essential usage context: the tool's purpose, a priority use case (before asking the user), and query formulation advice. It does not discuss edge cases or exclusions, but for a straightforward search tool, this is sufficiently complete.

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% with descriptions for all 5 parameters, so the baseline is 3. The description adds semantic value specifically for the 'query' parameter by clarifying that it expects natural language rather than keywords, with a concrete example. No additional insight is given for type, limit, agent_id, or min_similarity beyond the schema, but this meaningful addition for the most important parameter justifies a 4.

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 clearly states the tool searches memories via semantic similarity and returns top-N relevant items. The verb 'search' and resource 'memories' are specific, and 'semantic similarity' implies a distinction from time-based recall siblings. However, it does not explicitly name alternatives like recall_recent or recall_as_of, so it stops short of full differentiation.

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?

The description explicitly instructs to use this tool FIRST before asking the user to repeat information, establishing a clear priority. It also provides query formatting guidance (natural language vs keywords) with an example. It does not explicitly state when not to use it or mention alternative sibling tools, but the 'FIRST' directive is strong context.

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