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andresolbach

nodriver-mcp-server

Fill input

fill

Set the value of input, textarea, or select elements, clearing first and typing to trigger input events for React/Vue. For select, pick by value and dispatch change.

Instructions

Set the value of an input, textarea or select element.

Clears the field first, then types the value character by character so that input events fire and React/Vue-style controlled components actually register the change (assigning .value directly does not). For , the option is selected by value and a change event is dispatched.

Use type_text instead when you want to append to a focused field rather than replace its contents. For several fields at once, fill_form does it in one round trip.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uidYesElement uid from the most recent take_snapshot, e.g. "4_12". uids are invalidated whenever the page changes — if you get "unknown uid", take a fresh snapshot and retry with the new uid.
valueYesThe text to enter. For a <select> element this must match the option's value attribute, not its visible label.
include_snapshotNoAppend a fresh page snapshot to the response. Worth it when this action changes the page and take_snapshot would be your next call anyway — it saves a round trip, at the cost of a much larger response.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description thoroughly discloses behavior beyond annotations: it clears the field first, types character by character to trigger input events for React/Vue controlled components, and for <select> it selects by value and dispatches a change event. This adds significant value over the annotations (readOnlyHint=false, destructiveHint=false) and the schema, explaining the 'how' and 'why' of the tool's actions.

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 well-structured and concise: a clear opening sentence, a mid-section explaining the low-level behavior, and a final sentence covering alternatives. Every sentence contributes new information without redundancy or fluff, making it highly efficient and easy to parse.

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

Completeness5/5

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

Given the tool's complexity (interaction with controlled components) and the presence of a rich schema and output schema, the description covers all necessary context: what it does, how it does it, when to choose alternatives, and important side effects (clearing, event firing). No critical gaps remain, making it fully complete for an AI agent to select and invoke the tool correctly.

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%, and the parameter descriptions in the schema are already detailed (e.g., uid invalidation, select value attribute, include_snapshot behavior). The tool description does not add significant extra semantics beyond what the schema provides, so the baseline score of 3 is appropriate. There is no contradiction or missing parameter information.

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 clearly states the tool sets the value of input, textarea, or select elements, which is specific and distinct from sibling tools like type_text and fill_form. It also explains the mechanism (clears and types) and the target element types, making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly provides usage guidance: 'Use type_text instead when you want to append to a focused field rather than replace its contents' and 'For several fields at once, fill_form does it in one round trip.' This clearly delineates when to use this tool versus alternatives, which is exactly what high-quality usage guidelines should do.

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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