goldenratio-mcp

Golden ratio steps

golden_ratio_steps

Read-only

Calculate values stepped up or down by the golden ratio (× or ÷ 1.618), with optional units, to create type scales or pick adjacent sizes.

Instructions

Step any number up or down the golden ratio (x or / 1.61803398875), e.g. to pick a type scale or the next size. What the goldenratio.app Alfred workflow does.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "value": "<value>"
    },
    "name": "golden_ratio_steps"
  }
}

Input Schema

Name	Required	Description
`unit`	No	Unit suffix for the text column, e.g. "px".
`value`	Yes	Starting value, e.g. 16.
`steps_up`	No	Steps above the value (default 5).
`steps_down`	No	Steps below the value (default 5).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Nov 2, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that this is a pure golden-ratio stepping operation and references the Alfred workflow, but it does not add details such as rounding/precision or output formatting.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with the operation and golden-ratio constant front-loaded. The Alfred workflow reference is slightly ancillary but does not undermine the concise structure.

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 simple read-only calculation tool with a fully documented schema and no nested objects, the description gives enough to invoke it correctly. It does not explain return values or precision, but given the low complexity and absence of an output schema, this is a minor gap.

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 all four parameters are already documented in the input schema. The description explains the core calculation but does not add meaning, defaults, or constraints beyond what the schema provides.

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?

The description states a specific verb and resource: 'Step any number up or down the golden ratio' and gives the exact multiplier/divisor. It does not explicitly distinguish itself from siblings like golden_calculator or golden_spacing, so sibling differentiation is absent.

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?

It provides a clear use-case example ('to pick a type scale or the next size'), which gives useful context for when to use the tool. However, it does not state when to prefer it over sibling tools or any exclusions.

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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