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Glama

fanar_text_to_speech

Convert Arabic or English text into spoken audio files. Supports Qur'an recitation with named reciters and returns the saved file path.

Instructions

Speak Arabic or English text with a Fanar Aura voice and save it as an audio file; returns the file path. Qur'an recitation by a named reciter needs Fanar-Sadiq-TTS-1. About 20 requests a day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
modelNoFanar-Aura-TTS-2
voiceNoHamad
filenameNo
quran_reciterNo
response_formatNomp3

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well on output: it saves to a file and returns the file path. It also discloses a rate limit (~20 requests/day) and a model precondition. It omits permission/auth needs, whether files persist or are overwritten, and text-length limits.

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 dense sentences, front-loaded with the core action and output artifact, followed by the model caveat and quota. Little waste. The trailing 'About 20 requests a day' is terse and slightly ambiguous as to whether it is a hard cap or a soft guideline.

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?

For a 6-parameter tool with no annotations, no output schema, and 0% schema descriptions, the coverage of output form and rate limits is helpful but leaves voice/language pairing, format selection, and file-naming behavior undocumented anywhere. Adequate, not complete.

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 0% across 6 parameters, so the description must compensate and only partially does. It explains the model enum values and hints at quran_reciter, but says nothing about the 10-value voice enum (which voices suit Arabic vs English), filename, or response_format.

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 verb and resource: synthesize Arabic/English text into an audio file and return the path. That is unambiguous and clearly distinct from siblings like fanar_transcribe (the inverse) or fanar_chat. It stops short of naming an alternative sibling or contrasting explicitly, so it is not quite a 5.

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?

Gives a concrete routing condition: Qur'an recitation by a named reciter requires Fanar-Sadiq-TTS-1, implying Fanar-Aura-TTS-2 otherwise. It also surfaces a practical quota (~20 requests/day). No explicit when-not or alternative-tool guidance, but the model-selection rule is real, actionable context.

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