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

Beyond the annotations, the description discloses important behavioral traits: it 'May use stored data or AI generation,' tells the caller to 'review the result,' and notes the requirement for a Word Orb key, plan entitlement, and quota accounting. This adds substantial context beyond readOnlyHint and openWorldHint.

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 compact and every sentence adds value: purpose, generation behavior, prerequisites/quotas, and an alternative tool. It is front-loaded with the primary purpose before constraints.

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?

The description covers the main invocation considerations, including prerequisites, quotas, and behavioral expectations. There is no output schema, and the description does not detail the exact return structure, though 'definition' implies the expected content. This is a minor gap rather than a blocking omission.

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 term and age_group are already fully documented. The description reinforces the age_group concept ('adapted to the specified age group') but does not add new syntax, formats, or parameter-specific meaning 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 opens with a specific verb and resource: 'Request a definition adapted to the specified age group.' It clearly states the tool's core function and differentiates it from the sibling lookup_words by noting that define_term may use AI generation. This leaves no ambiguity about what the tool does.

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 gives a clear intended use for age-adapted definitions and provides one explicit alternative: 'Use lookup_words to avoid generated fallback.' It does not enumerate other alternatives or exclusions, but the main condition for choosing this tool is clear.

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