Skip to main content
Glama

Scaffold Preset

scaffold_preset

Create a new preset directory with manifest and token override scaffold by inheriting from a parent preset. Generates a ready-to-customize preset structure on disk for UI design systems.

Instructions

Create a new preset directory with manifest and token override scaffold, inheriting from a parent preset. Generates a ready-to-customize preset structure on disk.

Args:

  • preset_id (string): Kebab-case ID for the new preset (e.g. 'client-banking')

  • extends (string): Parent preset to inherit from (default: 'glassmorphic-base')

  • name (string): Human-readable display name

  • description (string): Short description

  • accent_color (string, optional): Override accent color in the scaffolded tokens

Returns: Path to new preset directory and files created.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
preset_idYesKebab-case ID for the new preset
extendsNoParent preset to inherit fromglassmorphic-base
nameYesHuman-readable display name
descriptionYesShort description
accent_colorNoOverride accent color in the scaffolded tokens
Behavior3/5

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

Annotations already indicate this is a non-readOnly, non-destructive, non-idempotent, non-openWorld operation. The description adds useful context beyond annotations: it specifies that the tool creates files on disk and generates a ready-to-customize structure. However, it doesn't mention important behavioral aspects like whether the operation requires specific permissions, what happens if the preset_id already exists, or any rate limits.

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 perfectly structured and concise: it starts with the core purpose, explains what it generates, then lists parameters with brief explanations, and ends with return information. Every sentence earns its place with zero wasted words, and the information is front-loaded appropriately.

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?

For a tool with 5 parameters, 100% schema coverage, and no output schema, the description is quite complete. It explains what the tool does, what it creates, the parameters, and what it returns. The main gap is the lack of output schema, but the description compensates by specifying the return value ('Path to new preset directory and files created'). It could be more complete by mentioning error conditions or prerequisites.

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 fully documents all parameters. The description's Args section repeats what's in the schema without adding significant additional meaning (e.g., it doesn't explain the significance of kebab-case format or provide examples beyond what's in the schema). The baseline of 3 is appropriate when the schema does the heavy lifting.

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 specific action ('Create a new preset directory with manifest and token override scaffold'), the resource ('preset'), and distinguishes it from siblings by specifying it creates a ready-to-customize structure on disk. It explicitly mentions inheritance from a parent preset, which differentiates it from tools like 'generate_tokens' or 'load_preset'.

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

Usage Guidelines4/5

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

The description provides clear context about when to use this tool: when you need to create a new preset directory with scaffolded files that inherits from a parent. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools (like 'generate_tokens' for creating tokens without directory structure).

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ncsound919/OG-Glass'

If you have feedback or need assistance with the MCP directory API, please join our Discord server