type_text

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

Discloses important behaviors: works on both platforms, targeting by label/text, verify's effect and extra cost (~200ms). However, omits details on error handling, special characters, or what happens if element is not found. With no annotations, the description carries the full burden but doesn't cover all edge cases.

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 concise sentences that front-load the main action and platform support, then add detail on targeting and verify. Every sentence is informative with no wasted words.

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 moderate complexity (4 params, simple input), the description covers the core use cases and key feature (verify). Lacks some edge case details but is sufficient for typical usage. No output schema required, so completeness is adequate.

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 coverage is 100%, so description adds limited value. It repeats the verify behavior already in the schema. The description's mention of 'target a field by its label/text' adds context for element_text but is not significantly beyond the schema's 'Label ou texte du champ à cibler'.

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?

Clearly states 'writes text in a field' with specific verb and resource. Distinguishes from sibling tools like tap, swipe, long_press by focusing on text input. Also notes cross-platform support (iOS and Android).

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?

Provides context for when to use: typing into fields, targeting by label, and using verify for autocomplete detection. Lacks explicit when-not-to-use or prerequisites (e.g., field must be focused), but the sibling set implies alternatives for other actions.

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