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type_text

Simulate keyboard input to type text character by character for GNOME desktop automation, enabling AI agents to interact with applications by entering text programmatically.

Instructions

Type text character by character.

Args: text: Text to type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'character by character' typing, which implies a sequential, potentially slower operation, but doesn't cover critical aspects like execution speed, error handling, or whether it simulates human-like typing. This leaves significant gaps in understanding how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and well-structured, with the core purpose stated upfront in the first sentence and parameter details neatly organized in an 'Args' section. Every sentence earns its place without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (simulating text input) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and low schema coverage, it lacks details on behavioral traits and parameter nuances, making it incomplete for optimal agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, with only one parameter 'text' documented minimally in the schema. The description adds a brief explanation ('Text to type'), which provides basic semantics but doesn't elaborate on constraints (e.g., length, special characters) or examples. Given the low schema coverage, this is a baseline compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Type text character by character') and specifies the resource ('text'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'key_press' or 'key_combo' that might also input text, leaving some ambiguity about when to choose this specific method.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'key_press' or 'key_combo' for text input. It lacks context about scenarios where character-by-character typing is preferred over other methods, offering minimal usage direction.

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

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