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Generate copy-paste TSX starter snippets for common UI compositions—app shells, dashboard rows, data grids, AI chat, and theming—wired with correct props.

Instructions

Copy-paste TSX for a common composition, wired with the correct props: an application shell, a dashboard row, a data grid, an AI chat, or the theming pattern.

Input Schema

NameRequiredDescriptionDefault
kindYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations present, the description carries the full load; it does disclose that the output is TSX already wired with the correct props, which is real behavioral context. However it says nothing about whether the snippet is read-only, how large it is, whether it spans multiple files, or any dependency on theming/tokens setup.

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?

One front-loaded sentence that states the deliverable first and then the supported variants; no filler or redundant restatement of the tool name.

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?

For a no-annotation, no-output-schema tool whose entire value is the returned artifact, the description should say more about the shape of the return (single file? multiple files? does it reference tokens or imports?). It conveys what is returned conceptually but leaves an agent guessing about output structure.

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

Parameters4/5

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

Schema coverage is 0% for the single 'kind' parameter, and the description compensates by mapping each enum value to a natural-language composition (app shell, dashboard row, data grid, AI chat, theming pattern). The mapping is loose at points—'dashboard row' vs the enum 'dashboard' and 'data grid' vs 'table'—so it is helpful but not airtight.

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?

Uses a concrete verb+resource ('Copy-paste TSX for a common composition') and enumerates the five composition kinds it serves, so an agent can tell it produces ready-to-use code rather than a component listing. It stops short of explicitly contrasting itself with get_component or get_block_source, which occupy adjacent ground.

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 enumerated compositions imply when the tool applies, but there is no explicit when-to-use/when-not statement and no routing to obvious alternatives like get_component (single component) or get_block_source (block source). The agent must infer the boundary from sibling names.

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