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

With no annotations, the description carries the full transparency burden and exceeds it. It discloses that audio is downloaded and run through Whisper large-v3, uses residential IPs to bypass datacenter blocklists, works without captions, returns text plus sentence timestamps, and states the pricing model and payment method. This is unusually complete behavioral disclosure.

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 longer than average but every sentence carries distinct information: operation, differentiation from caption scraping, platform coverage, technical method, IP provenance, return format, and pricing. It is front-loaded with the core purpose and then expands into necessary details, with no filler.

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?

Despite having no output schema and no annotations, the description tells an agent everything needed to invoke the tool correctly: what input to provide, what happens during execution, what the output will contain (full text plus sentence timestamps), and the commercial terms. The residential IP detail also explains why certain network scenarios are handled. Nothing critical is missing for a one-parameter tool.

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?

There is a single URL parameter with 0% schema description coverage, so the description must compensate. It effectively does so by specifying that the URL must point to a YouTube, TikTok, or Instagram video, which is the key semantic constraint beyond the bare schema type. It does not detail URL formats, but given a single obvious parameter, this is sufficient.

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 opens with a specific verb and resource: transcribe the actual audio of YouTube, TikTok, or Instagram videos. It explicitly contrasts with caption scraping and names the exact platforms, making the tool's function unmistakable even among many diverse siblings.

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 explains when this tool is appropriate: for videos without subtitles, in any language, and for platforms with no caption track. It implicitly tells the agent to use this when actual audio transcription is needed rather than caption extraction, though it does not explicitly name sibling alternatives or provide exclusion criteria beyond 'not caption scraping.'

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