search_memories

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

With no annotations provided, the description carries the behavioral burden and does it well: it discloses the matching algorithm, partial-word support, the TOON return format, and the 'Ø' no-match sentinel. It does not discuss side effects, but as a search operation the read-only nature is reasonably implied.

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 two concise sentences that front-load the operation, then add matching semantics, return format, and no-match behavior. Every sentence carries useful, non-redundant information.

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?

For a single-parameter search with no output schema, this definition is complete: it states what to pass, how matching works, what the response format is, and the sentinel for no matches. No critical operational gap remains.

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%, and the query parameter already includes a substring-matching example. The description reinforces fuzzy matching but adds little parameter-specific meaning beyond the schema, 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 clearly states the tool searches stored memories using fuzzy substring matching, with support for partial words and phrases. This distinguishes it from siblings save_memory and list_categories, which are write and list operations respectively.

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 gives clear context: use this tool when needing to retrieve memories by text query with fuzzy/partial matching. It does not explicitly name alternatives, but the search semantics are self-evident and do not conflict with the sibling tools.

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