Skip to main content
Glama

Fix how a word is pronounced

set_pronunciation_rule
DestructiveIdempotent

Use this when narration mispronounces a word, name or brand in a project's voiceovers. Returns the rule and the project's rule count after adding or replacing it (IPA or CMU phonemes, up to 500 rules) and syncing the pronunciation dictionary used for later synthesis. Not for re-voicing lines that already have audio.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wordYesExact word or phrase to match, up to 120 characters
alphabetNoPhonetic alphabet: ipa or cmu; defaults to ipa
phonemesYesHow to say it, in the chosen phonetic alphabet, up to 500 characters
projectIdYesProject whose narration to fix

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ruleYes
statusYes
projectIdYes
ruleCountYes
ruleCountIsLowerBoundYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / alphabet / description
      Previous value: -"Phonetic alphabet; defaults to ipa"New value: +"Phonetic alphabet: ipa or cmu; defaults to ipa"
    • changedInput schema / properties / phonemes / description
      Previous value: -"Phonetic pronunciation"New value: +"How to say it, in the chosen phonetic alphabet, up to 500 characters"
    • changedInput schema / properties / projectId / description
      Previous value: -"Tutorializer project id"New value: +"Project whose narration to fix"
    • changedInput schema / properties / word / description
      Previous value: -"Word or phrase to match"New value: +"Exact word or phrase to match, up to 120 characters"
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, and the description corroborates by stating it adds or replaces a rule. It adds real behavioral context beyond the schema: the 500-rule cap and the fact that the pronunciation dictionary is synced for later synthesis. It does not spell out what happens to the prior rule on replacement or any auth requirements.

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?

Three tight sentences, front-loaded with the when-to-use trigger, then effect, then exclusion. No filler and every clause carries information.

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 moderately complex mutation covered by annotations and an output schema (so return formatting needn't be explained), the description supplies the trigger, the effect, the rule cap and the dictionary-sync behavior. Only the replacement semantics and any permission requirements are left implicit.

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 100% schema description coverage, the schema already documents all four parameters, so the baseline is 3. The description references the IPA/CMU alphabets and the 500-rule cap, but the 500 is a system limit rather than a per-parameter detail, so the added parameter value is marginal.

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?

States a specific action (add or replace a pronunciation rule) and resource (a word/name/brand in a project's voiceovers), making the effect unambiguous. It does not explicitly name the sibling remove_pronunciation_rule, so an agent infers the boundary rather than being told it.

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?

'Use this when narration mispronounces a word' gives a clear triggering condition, and 'Not for re-voicing lines that already have audio' is an explicit exclusion. It stops short of naming the alternative tool an agent should reach for instead of re-voicing.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources