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babelwrap

io.github.soulfir/babelwrap-mcp

by babelwrap

babelwrap_fill

Fill a specified input field with a value using natural language descriptions or element IDs for precise targeting.

Instructions

Fill an input field with a value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYesThe active session ID.
targetYesNatural language description of the input field (e.g. "Email address field"). TIP: Pass an element ID from a previous snapshot (e.g. "input-email") to bypass LLM resolution entirely for instant, deterministic targeting.
valueYesThe value to fill in.
compactNoIf True, return a compact snapshot with minimal whitespace.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full burden. It fails to disclose behaviors like whether input is appended or replaced, handling of special characters, or needed focus state. This is insufficient for a mutation tool.

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 a single sentence that efficiently states the core purpose. Every word earns its place with no redundancy.

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

Completeness2/5

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

Given the tool's complexity, the description is too sparse. It doesn't mention required session state, error conditions, or interaction with page focus. The existence of an output schema mitigates the need to explain return values, but other gaps remain.

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?

Schema coverage is 100%, so the baseline is 3. The tool description adds no extra meaning beyond the schema, though the schema's target parameter includes a useful tip. No credit is given for repeating schema info.

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

Purpose5/5

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

The description 'Fill an input field with a value' uses a specific verb and resource, clearly distinguishing it from sibling tools like babelwrap_click or babelwrap_press. It leaves no ambiguity about the action performed.

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, nor does it mention prerequisites or exclusions. Usage is only implied by the tool's name.

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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