tokenize

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false, so the safety profile is clear. The description adds useful tokenization behavior—preserving order and including punctuation—but does not go much further beyond what the annotations provide.

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?

A single front-loaded sentence with no filler. It communicates the operation and output contract efficiently.

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?

With one parameter, an output schema, and annotations covering safety and idempotency, the description is largely complete. It adequately explains the output categories, though it does not explicitly mention deterministic behavior or input expectations, which are covered elsewhere.

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 input schema has full description coverage for the single `text` parameter, so the baseline is 3. The description implies the input is Estonian text but adds no format, length, or encoding details beyond the schema.

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: 'Split Estonian text into sentences and words.' It also clarifies the exact output semantics ('every token in order, punctuation included'), making the tool's purpose immediately distinguishable from linguistic-analysis siblings such as lemmatize or pos_tag.

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?

Usage is implied by the clear purpose, but there is no explicit guidance on when to use tokenize versus alternatives like analyze_morphology or syllabify. No exclusions or prerequisites are mentioned.

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