memory_recall

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

With no annotations provided, the description carries full burden. It discloses the cost ($0.002/call), wallet requirement, ranking method (cosine similarity), and return format (top-k with scores). However, it does not detail error handling, empty results, or authorization specifics beyond owner requiring a grant.

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 long, front-loaded with cost and requirement, then core functionality and outcome. Every sentence is essential, with no wasted words.

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 lack of output schema and annotations, the description explains the tool's purpose and parameters adequately. However, it does not detail the return structure beyond 'top-k matches with scores', missing specifics like whether it returns an array or object, what fields each match contains, or how scores are presented.

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 the schema already documents all parameters. The description adds context by explaining query as natural-language and k as top matches count, but does not provide additional meaning beyond what the schema states. Baseline 3 is appropriate.

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 recalls remembered text by similarity to a query using cosine similarity, and distinguishes itself from exact key retrieval. It also identifies itself as the retrieval half of wallet-scoped semantic memory, distinguishing it from sibling tools like memory_write and memory_read.

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 implies usage for similarity search rather than exact key, but does not explicitly state when to use this tool versus alternatives like memory_read (likely exact key) or memory_remember (write). It lacks explicit when-to-use or when-not-to-use guidance.

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