video_soundscape

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

With no annotations, the description carries the burden and does so well: it discloses download cost (~60s ≈ 1MB), clarifies probabilities are model outputs rather than facts, and instructs cross-checking against the visual. These are exactly the behavioral traits an agent needs and none are in structured fields.

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?

Dense and front-loaded: purpose, coverage, limitation, cost, and caveat each appear as a distinct clause with little waste. Slightly list-like but every sentence earns its place.

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?

Strong on behavioral and semantic context (what it detects, cost, output nature, caveats) but weak on the mechanics of its 7 undocumented parameters and no output schema is present. An agent knows what the tool is for but not precisely how to tune its invocation.

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 coverage is 0% across 7 parameters, and the description explains none of them — start/end, hop, window, top_k, min_prob are all left to the schema titles and defaults. The only implicit hint is the 60-second segment size. For a 7-param tool this leaves the agent guessing how to configure sensitivity and windowing.

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?

States a specific verb and resource — sound-event multi-labeling over an audio segment — and explicitly distinguishes it from transcription ('what was said'). The AudioSet 527-class / probability / timecode output description makes the operation unambiguous and separable from speech-oriented siblings like video_subs.

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?

Clearly frames the when-to-use ('not what was said') and gives concrete coverage examples (chewing, knocking, water) plus an explicit limitation (drinking/swallowing has no class). It doesn't name a specific alternative sibling for the speech case, so it stops short of a 5.

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