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rreusser

Observable Notebook Kit Debug MCP Server

by rreusser

SetInputValue

Update an Observable input widget's value and dispatch an input event, triggering reactive updates in dependent notebook cells.

Instructions

Set the .value property of an input widget in the Observable runtime (e.g., Inputs.range, Inputs.select, Inputs.text) and dispatch an input event, triggering reactive updates to dependent values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the cell containing the input widget (e.g., "slider" if defined as `slider = Inputs.range([0, 100])`)
valueYesThe value to set (number for range, string for text/select, boolean for toggle, array of strings for checkbox)
notebookNoTarget notebook (URL, path like "index" or "voronoi", or index like "0"). Optional if you've used FocusNotebook or only one notebook is connected.
timeout_msNoMaximum time to wait in milliseconds

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.2

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose the key side effects: setting the property, dispatching an input event, and triggering reactive updates. It could also mention failure modes or notebook-focus requirements, but the core mutating behavior is transparent.

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 dense sentence with no filler. It front-loads the action and target, then explains the side effect, and the examples are compact and useful.

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

Completeness4/5

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

Given that the schema fully documents parameters and the description clearly captures the operation and reactive consequence, the definition is adequate for invoking the tool. It does not describe return behavior or explicit error/edge cases, but those are not essential for a straightforward input setter.

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 description coverage is 100%, so the schema already documents all four parameters and their value types. The description adds only clarifying examples of widget kinds without going beyond the schema, so the baseline score of 3 is appropriate.

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 states a specific verb ('Set'), a precise target ('.value property of an input widget in the Observable runtime'), and concrete examples (Inputs.range, Inputs.select, Inputs.text). It clearly distinguishes this tool from read-oriented siblings like GetValue and GetValues.

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

Usage Guidelines3/5

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

The intended use is implied by the description: it is for programmatically setting widget values and triggering reactive updates, as opposed to simulating mouse input. However, it does not explicitly name alternatives or state when not to use this tool, so the agent must infer the selection from context.

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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