design_preview
Look up a pre-built object screen in React or Vue. Returns its hosted URL, recorded content hash and exact local reproduction calls.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| object | Yes | ||
| context | No | detail | |
| framework | No | react |
Look up a pre-built object screen in React or Vue. Returns its hosted URL, recorded content hash and exact local reproduction calls.
| Name | Required | Description | Default |
|---|---|---|---|
| object | Yes | ||
| context | No | detail | |
| framework | No | react |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower; the description adds genuinely useful output context — hosted URL, recorded content hash, and reproduction calls — which matters because no output schema exists. It omits any note on auth, rate limits, or what a missing/uncached preview looks like.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences, zero filler, with the lookup action front-loaded and the return payload enumerated afterward. Every clause carries information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description usefully covers return values in the absence of an output schema, and the read-only annotations cover safety. However, two of three parameters (object, context) are entirely undocumented and there is no usage guidance, leaving the agent to guess at valid screen/context combinations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and all three parameters are bare enums, so the description must compensate. It only surfaces the framework axis ("React or Vue") and says nothing about the object enum values or the seven context values (detail, list, form, timeline, card, inline, workflow).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ("Look up") and resource ("pre-built object screen in React or Vue"), which is concrete enough to distinguish it from generic siblings like object or structuredData_fetch. It stops short of explicitly naming a sibling it differs from, so it lands at clear-but-not-routing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use or when-not-to-use guidance, and no mention of alternatives such as object, viz_render, or catalog_list. The agent must infer the usage context purely from the tool name and description.
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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