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

Annotations already declare this is read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond those hints by explaining that the tool handles fuzzy, transliterated, and Hebrew input and that it returns validity information and canonical names. No contradiction with annotations.

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 sentences, no filler, with the core purpose first and parenthetical examples that illustrate rather than distract. Every sentence earns its place.

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 there is no output schema, the description still communicates the key return information the agent needs: validation status and canonical names. It does not detail result shapes or how the 'limit' interacts with results, but those are largely inferable from the schema and the described behavior.

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 only 33%, with only the 'type' parameter documented. The description compensates for the ambiguous 'name' parameter by showing example inputs and describing what kinds of names are accepted, while 'limit' and 'type' are sufficiently defined by their schema constraints.

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 clear action (autocomplete and identify), the resource types (book title, reference, author, topic, person), and the outcome (validity check plus canonical names). It is specific and easy to parse, though it does not explicitly differentiate itself from sibling tools like parse_reference or dictionary_autocomplete.

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 when to use the tool: when input is partial, misspelled, transliterated, or Hebrew. However, it never names alternatives or says when not to use it, so an agent must infer the distinction from sibling names rather than being given explicit guidance.

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