generate_interfaceUse to generate a new Gravity AI UI composed interface from a prompt. This calls the public generator with the server OpenAI configuration and does not save or publish the result.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | Natural-language prompt for the interface to generate. | |
| conversationId | No | Optional stable conversation id for this generation. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description discloses notable behavioral details: it 'calls the public generator with the server OpenAI configuration' and 'does not save or publish the result.' This adds valuable context about external calls and persistence, though it does not cover all potential side effects or error conditions.
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?
The description is two sentences, direct, and front-loaded with the primary action and target. Every clause contributes meaningful information without redundancy or filler.
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?
For a tool with two simple parameters and no output schema, the description covers the main purpose, invocation context, and key behavioral caveats (no save/publish). It could briefly mention return behavior or alternatives, but the core usage is adequately complete for an agent.
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?
The input schema already provides 100% coverage for both parameters, including descriptions for 'prompt' and 'conversationId.' The tool description adds little semantic detail beyond the schema, only mentioning 'from a prompt,' which is already present in the schema.
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?
The description clearly states the action: 'generate a new Gravity AI UI composed interface from a prompt.' It distinguishes itself from siblings like get_interface, refine_interface, and search_interfaces by focusing on creation from a prompt rather than retrieval or refinement.
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?
The description explicitly opens with 'Use to generate a new...' providing clear context for when to invoke it. However, it does not mention when not to use it or explicitly name alternatives among the sibling tools, leaving some ambiguity for an agent comparing options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: generate creates new interfaces, get fetches by specific id, refine modifies existing payloads, and search discovers by keywords. No two tools have overlapping boundaries, making it easy for an agent to select the right one.
All tools follow a verb_noun pattern with underscores (generate_interface, get_interface, refine_interface, search_interfaces). The only minor deviation is the pluralization of 'interfaces' in search_interfaces, which is a common exception for discovery operations and does not hinder readability.
With only 4 tools, the server is tightly scoped for the domain of Gravity AI UI generation and retrieval. Each tool serves a necessary role without redundancy or bloat, fitting well within the ideal range.
The tool surface covers the complete lifecycle for a design generation service: create, read, update, and discover. While there is no explicit delete or publish, those actions are intentionally excluded per the descriptions, so there are no dead ends for typical workflows.