list_vectors

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

The description discloses the return format ({ vectors, next_cursor }) and mentions optional filtering and pagination. Without annotations, it provides basic transparency but lacks details on error conditions, rate limits, or prerequisites (e.g., dataset context).

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 that packs the core functionality, optional features, and return format. It is concise and front-loaded, though the mismatch with the schema reduces its effectiveness.

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 empty schema and no annotations, the description covers the basic operation and return type. However, it omits details like required dataset identification, error handling, and the impact of additionalProperties being true in the schema, leaving gaps for agent invocation.

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 description mentions a metadata filter, page limit, and cursor, but the input schema has zero parameters. This adds misleading meaning beyond the schema, and with 100% schema coverage (of no params), the baseline expectation is not met. The description does not clarify how to pass these filters without defined 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 it lists vector records with id and metadata, and mentions optional filtering and pagination. This distinguishes it from siblings like get_vector (single retrieval) and query_vectors (similarity search). However, the described parameters are not present in the empty input schema, causing some confusion.

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 notes it is useful for enumerating or auditing stored memories, providing a use case. It does not explicitly exclude other scenarios or compare with sibling tools, leaving the agent to infer when to use which.

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