search_memory

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

No annotations are provided, so the description must carry behavioral transparency. It only states that it searches and returns chunks, without disclosing details like result ordering, limits, or whether it has any side effects. This is minimal and relies on the agent's assumptions.

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 a single sentence with no redundant content and the verb is front-loaded. It is concise and to the point, though it could have included more detail without becoming verbose.

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?

The tool is simple, but the description's 'return relevant chunks' is vague; it doesn't explain the format, size, or criteria of returned chunks. Since there is no output schema, the description should clarify the return value more fully.

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?

The schema has one required 'query' string with no description, and the description provides no additional explanation of what the query should be or how it is interpreted. With 0% schema description coverage, the description fails to compensate, leaving the parameter's meaning entirely to its name.

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 uses a specific verb 'search' and names the resource 'memories in the vector store', and clarifies the outcome 'return relevant chunks'. This clearly distinguishes it from the sibling 'save_memory', which is a write operation.

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?

There is no explicit guidance on when to use this tool versus save_memory. The description merely states what it does, leaving usage to implication rather than spelling out conditions or alternatives.

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