memory_search_multi

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 deduplication by chunk, max-score sorting, and cost advantage. It lacks details on error behavior, but for a read-only search operation it offers solid transparency.

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 concise sentences with no filler. The most critical information (what, why, how) is front-loaded, and each sentence contributes either purpose, usage guidance, or behavioral detail.

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 absence of annotations and output schema, the description covers purpose, usage guidance, behavioral specifics (dedup, sorting), and cost considerations. It fully equips an agent to decide when to invoke and what to expect, especially with sibling memory_search as a frame of reference.

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 descriptions cover all three parameters (100% coverage), establishing a baseline. The description adds practical query-construction guidance (vary vocabulary, split compounds, drop prefixes) and notes that more than 2-5 queries is wasted work, enriching the queries parameter semantics beyond the schema.

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's function: running multiple query variants through memory search in a single call. It distinguishes itself from the sibling memory_search by explaining the batching advantage and when it's appropriate.

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?

It explicitly specifies when to use this tool (when initial memory_search underperforms, with concrete failure indicators like weak top score or missing fragment) and how to construct queries. It also contrasts with multiple separate memory_search calls by highlighting cost efficiency.

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