Machine-translate missing entries

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

With no annotations, the description carries the full burden and does so well: it discloses the external dependency (@anthropic-ai/sdk + ANTHROPIC_API_KEY), that output lands as drafts needing human review, partial-failure semantics (unanswered batches appear in failed while other writes persist), and retry economy ('only asks for what is left'). These are exactly the traits an agent cannot infer from structured fields.

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?

Four sentences, each contributing distinct information, with purpose front-loaded and the dryRun caveat last. Dense but every sentence earns its place; minor cost is that the dependency and review caveats are packed into the opening sentence.

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?

An output schema exists, so return values need not be explained, yet the description still clarifies the `failed` field's meaning and the retry contract. Combined with dependency and draft-review disclosure, an agent has everything needed to call this correctly and interpret failure.

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 root, dryRun, and locales are already documented in the schema. The description restates dryRun's effect but adds no syntax, defaults, or format detail beyond it; the baseline of 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb+resource ('Fill missing translations') and names the configured provider, making the action unambiguous. It does not explicitly distinguish itself from the closest siblings such as verbaly_missing or verbaly_write_drafts, so an agent must infer that this is the provider-calling variant.

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?

Clear context is given: use it to fill missing translations, and dryRun lists candidates without calling the provider, which effectively contrasts the two modes. The note that drafts go to `verbaly review` and 'no tool here can approve' them prevents a wrong tool choice. It stops short of naming sibling tools as alternatives for listing (e.g. verbaly_missing).

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