Analyze Audio Realtime

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'real-time audio analysis' but doesn't clarify operational aspects: whether it requires an active audio stream, how results are returned (e.g., streaming vs. batch), latency expectations, or error handling. For a real-time analysis tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Perform real-time audio analysis') and specifies key features. There is no wasted text, repetition, or unnecessary elaboration, making it highly concise and well-structured for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (real-time audio analysis with multiple parameters) and lack of annotations and output schema, the description is minimally adequate. It covers the basic purpose and features but lacks details on behavior, usage context, and output format. With no output schema, the description should ideally hint at return values (e.g., what analysis results look like), but it doesn't, leaving gaps for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all four parameters with descriptions, defaults, and an enum for analysis_type. The description adds minimal value beyond the schema, mentioning 'pitch detection and spectral features' which map to two boolean parameters but without additional context. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Perform real-time audio analysis with pitch detection and spectral features.' It specifies the action ('analyze'), resource ('audio'), and key capabilities ('pitch detection and spectral features'), distinguishing it from siblings like audio_start_capture (which captures audio) or midi tools. However, it doesn't explicitly differentiate from all siblings (e.g., configure_musical_intelligence might be related).

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether audio capture must be active), compare it to siblings like audio_start_capture or configure_musical_intelligence, or specify scenarios where it's appropriate. Usage is implied by the name and description but not explicitly stated.

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