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Glama

Measure a message's sound

sound
Read-onlyIdempotent

Analyzes how a Rowih message is spoken for writing or checking verse, returning each line’s measure, syllables, stresses, line endings, and onset/vowel echoes plus diagnostics; read-only.

Instructions

The sound of a message as spoken, for writing or checking verse: for each line its measure, syllables, stresses, end and its echoes of onset and vowel, with the end echoes between lines. Returns sound (lines and end echoes) and diagnostics. Nothing in it changes what a message means. Read-only.

Input Schema

NameRequiredDescriptionDefault
textYesa whole Rowih message as sent, its envelope line included, in the transliteration (Latin letters) or the native digital form

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.1.4
    • changedInput schema / properties / text / description
      Previous value: -"a message of the language, in the transliteration or in the native digital form"New value: +"a whole Rowih message as sent, its envelope line included, in the transliteration (Latin letters) or the native digital form"
  2. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so safety is covered. The description adds genuine value beyond that by disclosing what is returned ('sound (lines and end echoes) and diagnostics') and reassuring that it does not alter meaning, which matters given there is no output schema. It does restate read-only, which is redundant but harmless.

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?

Two sentences, purpose front-loaded, no filler. The middle clause listing measured features is dense and slightly hard to parse, but every sentence earns its place and nothing is wasted.

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 one-parameter, no-output-schema tool with annotations already covering the safety profile, the description is nearly sufficient: it explains the outputs and diagnostic return. Only the absence of guidance about related tools or error behavior keeps it short of full completeness.

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?

With a single parameter and 100% schema description coverage, the schema already fully documents that `text` must be a whole message including the envelope line, in transliteration or native form. The description adds nothing about that parameter's format or constraints, so the baseline 3 applies.

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 names a specific operation (measure the sound of a message as spoken) and enumerates the measured quantities: measure, syllables, stresses, line-end and onset/vowel echoes. This distinguishes it from siblings like parse, tokenize, or speak, though it never names those siblings explicitly. The poetic phrasing ('its echoes of onset and vowel') is slightly opaque but the verb+resource is unambiguous.

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 clause 'for writing or checking verse' gives a use-case context that implies when to reach for this tool. However, it offers no explicit when-not guidance and does not point to any alternative sibling (e.g., analyze, tokenize, speak) for related tasks, leaving selection to inference.

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