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

With no annotations provided, the description carries full burden. It discloses key behaviors: returns vector and dimension, has no side effects, does not index notes. It also mentions truncation via the schema. However, it could be improved by noting potential error conditions or cost implications.

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 exceptionally concise: two sentences that cover purpose, usage guidelines, side effects, and alternatives without extraneous information.

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 (one parameter, straightforward task), the description comprehensively covers purpose, usage context, output, and limitations. No output schema exists, but the description states what is returned.

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?

There is only one parameter 'text' with schema description covering truncation (100% coverage). The description does not add further semantics beyond the schema, but the baseline 3 is appropriate since the schema already provides sufficient detail.

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: creating a vector embedding for a short text and returning the vector and its dimension. It also distinguishes itself from the sibling tool 'index_all' by specifying that it does not index notes.

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 explicitly states when to use the tool (diagnostics, manual similarity checks, validating setup) and provides a clear alternative for batch embeddings: 'index_all with with_embeddings=true'. It also notes that the tool has no side effects.

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