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

The annotations already declare read-only, non-destructive, closed-world behavior, so the safety profile is covered. The description adds useful operational constraints beyond annotations: results are ranked best-first, capped at 50, and do not page or filter.

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?

Two short sentences, front-loaded with the core purpose and followed by the key behavioral constraints. There is no waste, and the most important scoping information appears first.

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 rich annotations, full schema coverage, and an output schema, the description supplies what an agent needs to invoke the tool correctly. It covers scope, ranking, result cap, and the absence of paging or filtering.

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 parameters are already well documented. The description repeats key semantics such as 'one notebook,' 'either language,' and 'at most 50,' but adds little beyond what the schema already provides.

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 states a specific verb and resource: search words by query in one notebook, returning best matches first. It clearly distinguishes this from sibling tools like list_words and get_word by framing the operation as query-based ranked search rather than listing or retrieving by id.

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?

It gives clear context for use: a query within a single notebook, in either language, with best matches returned first. It does not explicitly name alternatives such as list_words or get_word, nor does it state when-not-to-use this tool, so it falls short of full routing guidance.

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