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

The description adds substantial behavioral detail beyond the readOnlyHint annotation: coverage differs by language, existence is judged per requested language, 'exists: false' is a successful outcome with additional fields, and the site's index is regenerated on every deploy. It also warns against retrying, which is genuine behavioral guidance an agent could not infer from the schema or 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?

The description is dense but structured: action first, then slug rules, coverage, existence semantics, and a retry warning. Every sentence contributes meaningful information, though the length is substantial. It is front-loaded with the core purpose and avoids fluff, but is not as compact as it could be.

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?

For a lookup tool with no output schema, the description covers edge cases well: language-specific existence, non-uniform coverage, the exists:false result shape, also_published_in, nearest numbers, and the no-retry rule. The only gap is that it never explicitly describes the success response when exists:true beyond the title's promise of an article URL, but overall this is a complete and actionable definition.

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?

Although schema description coverage is 100%, the description enriches both parameters. For 'number' it supplies slug patterns and an outlier ('828'); for 'language' it explains defaults, supported languages, and coverage variance. This goes beyond the schema's basic pattern and example descriptions.

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 precise verb and resource: 'Resolve a specific angel number... to its Anahana article URL, in any of 24 languages.' It names specific examples ('111', '1234', '22') and states the slug conventions, making the tool's purpose unmistakable and clearly distinct from the sibling tools get_article and search_content.

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 clearly establishes the tool's use case: resolving an angel number to an article URL, with language and coverage semantics explained. It also gives an important operational instruction ('Do not retry it'). However, it does not explicitly contrast this tool with the sibling tools or state when not to use it, so it stops short of a full when/when-not explanation.

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