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Multimodal Audio Emotion Valence Detector - Production-grade acoustic vocal emotion and frustration detector for voice AI agents. Calculates emotional valence (-1.0 to +1.0) and acoustic arousal to trigger de-escalation protocols.
Single tool with critical definition gaps. Tool name 'detect_audio_emotion' lacks action verb prefix (should be 'analyze_audio_emotion' or 'detect_emotion_from_audio'). Description is adequate (89 chars, within 10-1024 range) but parameters lack descriptions entirely, all three numeric inputs (pitch_hz_variance, speech_rate_syllables_sec, amplitude_jitter) have no parameter-level documentation explaining their purpose, valid ranges, or units beyond the schema type. Output schema is completely undocumented, LLM cannot predict what fields to expect or how to chain results. No error handling guidance. Defaults are present but lack justification.
Detects customer emotional valence and vocal frustration from speech prosody.
All three input parameters lack descriptions. LLM cannot understand what pitch_hz_variance, speech_rate_syllables_sec, and amplitude_jitter control or what valid ranges are.
Output schema completely undocumented. Response includes 8 fields (detection_id, acoustic_arousal_score, emotional_valence_score, pitch_variance_hz, speech_rate_syllables_sec, frustration_detected, recommended_agent_persona_adaptation, barge_in_priority_boost) but LLM has no schema definition to predict structure or downstream chaining.
Tool name 'detect_audio_emotion' does not follow verb_noun convention clearly. Ambiguous whether it detects emotion FROM audio or detects audio THAT IS emotional. Should be 'analyze_audio_emotion' or 'detect_emotion_from_speech'.
No error handling or recovery guidance. If client.detect_audio_emotion() fails or returns invalid data, LLM has no actionable error message or retry strategy.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 38 | 2026-07-28+ | v2 |
Parameter defaults (pitch_hz_variance=85.4, speech_rate_syllables_sec=6.2, amplitude_jitter=0.045) are unexplained. LLM cannot determine if these are sensible defaults or if they should be overridden for specific use cases.