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OnStartups

Agent.ai MCP Server

by OnStartups

interactive_ui

Create interactive UI components like dashboards, forms, and reports as part of your workflow. Provide instructions, select a model and theme, and receive a validated render-spec for display.

Instructions

Generate interactive UI as a step in your workflow — dashboards, forms, multi-section reports. Pick a model + theme, write the prompt, and get back a validated render-spec the runner can display.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instructionsYesDescribe the UI you want the model to emit. Reference prior step output with {{var_name}}.
modelNoWhich model authors the spec. Opus is the default; cheaper models trade fidelity for cost.claude-opus-4-7
themeNoVisual theme applied to the rendered Frame. Default matches the rest of the app; pick a preset from the options to override.default
sidebar_progressNoWhen the spec emits a Sidebar block, display a 'sections complete' counter in its header.
output_variable_nameYesVariable that holds the rendered directive ({spec, theme, ...}) for downstream steps.ui_spec
Behavior3/5

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

Without annotations, the description carries the transparency burden. It states the output is a validated render-spec and mentions model fidelity/cost trade-offs, providing moderate behavioral insight. However, it does not disclose safety, reversibility, or error handling behaviors.

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 efficient sentence that front-loads purpose and covers key points (generate, select model/theme, write prompt, get spec). Every clause is meaningful 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?

Despite no output schema, the description does not detail the render-spec structure or validation process. It omits how the output integrates with the runner. Given the tool's 5-parameter complexity and missing annotations, more context on output and workflow integration is needed.

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 description summarizes model and theme selection and mentions 'write the prompt', but does not add extra meaning beyond the schema's descriptions (e.g., instruction format or variable referencing). No new context is provided.

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 generates interactive UI as a workflow step, specifying concrete outputs like dashboards, forms, and multi-section reports. It distinguishes from siblings like 'generate_image' or 'shared_render_tabbed_report' by focusing on validated render-specs for the runner.

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 description implies usage as a workflow step but offers no explicit guidance on when to prefer this tool over alternatives (e.g., 'output_formatter' for formatting or 'invoke_agent' for general generation). No when-not-to-use or prerequisite conditions are mentioned.

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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