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nmassi

glyphs-mcp

by nmassi

rmx_batch

Apply RMX filters to multiple glyphs at once, enabling batch harmonization, tuning, scaling, or monospacing for efficient type adjustments.

Instructions

Apply an RMX filter to multiple glyphs at once.

RECIPE: For multi-glyph scaling, call get_recipe("scale_proportions") first.

Args: filter_name: One of "harmonize", "tune", "scale", "monospace" glyph_names: List of glyph names to process params: Filter-specific parameters (same as individual tool params) master_id: Optional master ID

Examples: "Harmonize all lowercase" → rmx_batch("harmonize", ["a","b",...,"z"], params={"mode": "harmonize"})

"Make all caps 20% wider" →
rmx_batch("scale", ["A","B",...,"Z"], params={"width": 120})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo
master_idNo
filter_nameYes
glyph_namesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are present, so the description carries the burden. It adds useful non-obvious context: a get_recipe prerequisite for scaling, optional master_id, and the relationship to individual tool params. Still, it does not disclose mutation/undo behavior, return values, or failure handling for a potentially destructive batch operation.

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 well structured: a one-line definition, a recipe tip, labeled args, and two relevant examples. It is slightly longer than necessary, but every section contributes actionable information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An agent can likely construct a valid batch call from this description because it covers the top-level arguments and gives examples. However, without annotations or an output schema, important context is missing: exact per-filter parameter schemas, return format, error behavior, and whether the operation is reversible.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates by listing allowed filter_name values, explaining glyph_names, defining params as filter-specific, and marking master_id optional. The examples with params keys like mode and width add concrete meaning beyond the bare schema.

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?

Describes a specific action: apply one of four named RMX filters to multiple glyphs at once. The batch semantics clearly distinguish it from the individual rmx_harmonize, rmx_scale, rmx_tune, and rmx_monospace siblings, and the examples reinforce the exact call pattern.

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 this tool by focusing on multiple glyphs and gives a workflow hint for multi-glyph scaling with get_recipe. However, it does not explicitly contrast it with the individual RMX tools or state when not to use batch processing, so the decision guidance is incomplete.

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