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tool_design_voice

Generate speech from text using descriptive voice keywords (e.g., whisper, female, low pitch) for one-off voices without saving a profile. Specify text and instruct keywords to produce custom TTS output.

Instructions

Generate speech using voice design keywords only (no cloned voice).

Same ASMR params as synthesize_speech. Use this when you want a one-off voice without persisting a profile. For reusable voices, clone first with clone_voice_from_audio then call synthesize_speech with voice_name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to speak (same as synthesize_speech).
speedNoSpeech rate. 1.0 = normal.
reverbNoReverb mode: 'none' (off), 'small_room' (ASMR-tight, ~18% mix, HF-damped), 'large_room' (spacious, longer tail). None = off. Default = off.
instructYesVoice design keywords (REQUIRED for this tool). English OR Chinese, comma+space separated. Examples: 'whisper, female, low pitch' (ASMR), 'male, young adult, british accent', '女,低音调' (Chinese).
languageNoTarget language. Default: 'Italian'.Italian
num_stepNoDiffusion steps. 32 = default.
period_sNoL<->R period in seconds. ASMR sweet spot: 2-3s.
stereo_panNoStereo panning mode for ASMR. One of: 'center' (mono -> stereo, equal L/R), 'L' (hard left, R muted), 'R' (hard right, L muted), 'L<->R' (alternating L/R, ASMR 'whisper in each ear' effect, sweet spot period_s=2-3s), 'L->R' (slow sweep L to R then back, sawtooth), 'R->L' (slow sweep R to L then back, sawtooth). None = no panning (passthrough).
output_pathNoOutput WAV path. Default: data/outputs/<ts>.wav.
guidance_scaleNoCFG scale. 2.0 default.
reverb_dampingNoReverb HF damping. 0.5 default.
binaural_beat_hzNoBinaural beat frequency in Hz (L channel = 200Hz carrier, R channel = 200Hz+beat). 0 = off (default, RECOMMENDED for clean output). Perceived as brainwave entrainment: 4-8 Hz = theta-alpha (sleep/relax), 10-15 Hz = alpha-beta (focus), 15-40 Hz = beta (alert). Carrier amplitude is fixed at 0.0005 (-66dBFS, sub-audible).
lowpass_cutoff_hzNoLowpass cutoff in Hz for warmth/intimacy. 0 = off. ASMR sweet spot: 5000-7000 Hz (cuts above 7kHz for 'headphones' feel).
highpass_cutoff_hzNoHighpass cutoff in Hz for DC/sub-bass cleanup. Default = 60 Hz (always on). 0 = off. ASMR standard: 60-80 Hz to remove room rumble without affecting voice.
silence_padding_msNoMilliseconds of silence inserted between sentences (split on . ? !). Position is weighted by sentence length. 0 = off. ASMR sweet spot: 400-800 ms.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden, and it clearly discloses the key non-obvious trait: this tool does not persist a voice profile and does not use a cloned voice. It does not explicitly describe the return value or file-writing behavior, though those are partially implied by the output_path parameter.

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 short sentences, no filler, with the core purpose and key distinction first, then usage guidance and alternative workflow. Every sentence earns its place.

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 15-parameter tool with no annotations and no output schema, the description covers selection, invocation, and routing to the right sibling, while the schema covers parameter details. It stops short of stating what the tool returns or writes, which would make it fully complete, but the output_path parameter fills most of that gap.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema by tying the parameter set to synthesize_speech ('Same ASMR params') and by clarifying that instruct is a keyword-based design, not a cloned voice reference. That cross-tool context is genuinely useful and not already in the 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?

The first sentence states a specific action ('Generate speech') and a specific resource/method ('voice design keywords only (no cloned voice)'), which immediately distinguishes it from cloned-voice synthesis. It also names the sibling tools that share the ASMR parameter space, so the agent can tell this tool apart from synthesize_speech and clone_voice_from_audio.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to use this tool for a one-off voice without persisting a profile, and it gives the alternative workflow: clone first with clone_voice_from_audio, then call synthesize_speech with voice_name for reusable voices. This is direct when-to-use and when-not-to-use guidance.

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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