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analyze_audio

Analyze speech audio to detect the speaker's emotional state, energy level, and stress indicator. Extract basic audio features like pitch and duration.

Instructions

Analyze audio for emotion and basic features.

This tool analyzes speech audio to detect the speaker's emotional state and extract basic audio features. For Lite tier, ASR is not included, so provide the 'text' parameter if you have a transcription.

Args: audio_path: Path to the audio file (WAV format supported) text: Optional transcription text for context

Returns: Dictionary containing: - transcription: None for Lite tier (ASR not included) - note: Information about Lite tier limitations - emotion: Object with primary emotion, confidence, secondary emotion, scores - speaker_state: Object with energy_level and stress_indicator - features: Raw audio features (duration, pitch, energy, etc.)

Example: { "transcription": null, "note": "Lite tier does not include ASR...", "emotion": { "primary": "happy", "confidence": 0.85, "secondary": "excited", "scores": {"happy": 0.8, "excited": 0.6, ...} }, "speaker_state": { "energy_level": "high", "stress_indicator": "low" }, "features": {...} }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_pathYes
textNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It transparently details Lite tier limitations, return structure, and example output. However, it does not disclose prerequisites like file size limits or authentication requirements.

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?

The description is well-structured with Args, Returns, and Example sections, front-loading the purpose. It is appropriately sized for a complex tool, though minor trimming could improve conciseness.

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?

Given the complexity, the description covers inputs, outputs, and limitations comprehensively. It details the return dictionary structure and tier-specific behavior, making it complete enough for effective use.

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 description coverage is 0%, but the description adds significant meaning: explains audio_path expects WAV format, text is optional transcription. This compensates for the empty schema descriptions.

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 clearly states the tool analyzes audio for emotion and basic features, with specific verb 'analyze' and resource 'audio'. It distinguishes from siblings by focusing on emotion and basic features, but does not explicitly contrast with sibling tools like detect_sarcasm or full_analysis.

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 description provides moderate guidance by explaining when to provide the 'text' parameter (for Lite tier without ASR), but does not specify when not to use this tool compared to alternatives like full_analysis or assess_urgency.

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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