recall

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

With no annotations, the description fully discloses behavior: it combines full-text search with relevance scoring, specifies that top matches return exact content while others return summaries, and explains that linked memory titles are included. This goes beyond a simple 'search' and informs the agent about result granularity and graph traversal.

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 three sentences, each earning its place: purpose is stated first, then a usage example, then output behavior. No redundant information or filler.

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 tool's simplicity (2 params) and the presence of an output schema, the description is complete enough. It covers what the tool does, when to use it, and what to expect in results, without needing to restate return fields. It is well-rounded and tightly written.

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%, with query and branch both documented. The description adds a natural-language example but does not meaningfully extend the schema's definitions; baseline 3 is appropriate because the structured data already explains parameters.

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 verb and resource: 'Search the user's private memory wiki with a natural-language query.' This is specific and distinguishes it from sibling tools like list_memories (which would list all memories) or memorize (which writes).

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 provides a concrete use case ('what did I say about the Rust borrow checker last month?') and says 'Use this to answer questions like...', which gives clear guidance on when to invoke it. It does not explicitly list alternatives or exclusions, but the context is clear enough for an agent to choose it for semantic memory search over list/forget tools.

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