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HalidSaglam

saglitzdesign-mcp

by HalidSaglam

Generate Elevation System

generate_elevation_system
Read-onlyIdempotent

Generate a cohesive elevation ramp with semantic level names, CSS custom properties, Tailwind @theme, and dark-mode guidance. Replaces hand-tuned shadows with one token per level.

Instructions

Generate a cohesive elevation / box-shadow ramp (layered ambient + direct light) with semantic level names (flat…modal), as CSS custom properties and Tailwind @theme, plus dark-mode guidance. Deterministic. Use one shadow token per level instead of hand-tuning shadows per component.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hueNoOptional shadow tint as 'H S%' e.g. '220 40%' for a cool cast (default neutral black)
levelsNoNumber of raised levels (default 5)
strengthNoOpacity multiplier 0.5–1.5 (default 1)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.28.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already signal read-only, idempotent, and non-destructive behavior. The description adds useful context beyond annotations by stating the tool is deterministic and by describing what the output includes (CSS custom properties, Tailwind @theme, dark-mode guidance). No contradiction with annotations.

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 compact, front-loaded with the primary purpose, and each sentence earns its place. The deterministic note and the one-token-per-level guidance are valuable without bloating the text.

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?

With no output schema, the description appropriately explains what the tool returns: CSS custom properties, Tailwind @theme tokens, and dark-mode guidance. It also communicates the semantic naming scheme. It could be more explicit about output structure or examples, but it is sufficiently complete for a deterministic, read-only generation tool.

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 schema already fully documents hue, levels, and strength. The description does not add much parameter-level detail, but it does clarify the overall purpose of the generated ramp and the semantic naming convention, which is enough to maintain the baseline score.

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 identifies a specific deliverable: a cohesive elevation/box-shadow ramp with semantic levels, CSS custom properties, Tailwind @theme integration, and dark-mode guidance. It is distinct from sibling generators like generate_color_system or generate_type_scale because it names its exact output domain and format.

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 when to use the tool: when you need elevation tokens rather than hand-tuning per-component shadows. However, it does not explicitly mention alternatives or state when not to use it, leaving tool-selection guidance mostly implicit.

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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