transcribe_video

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: the tool downloads/extracts audio, generates multiple output formats (TXT, JSON, Markdown), and has specific system dependencies (yt-dlp, whisper, ffmpeg). It doesn't mention rate limits, error handling, or processing time expectations, but provides substantial operational context.

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 efficiently structured in two sentences: the first states the core functionality and scope, the second covers implementation details and dependencies. Every element serves a purpose with no wasted words, and the most important information (what the tool does) is front-loaded.

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?

For a tool with 4 parameters, 100% schema coverage, and no output schema, the description provides good contextual completeness. It covers the tool's purpose, scope, implementation approach, output formats, and dependencies. The main gap is the lack of output schema, but the description mentions the output formats, which partially compensates. It doesn't describe error cases or performance characteristics.

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?

The input schema has 100% description coverage, so the schema already documents all parameters thoroughly. The description adds some context about the platforms supported and output formats, but doesn't provide additional parameter-specific semantics beyond what's in the schema. This meets the baseline expectation when schema coverage is complete.

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 specific action ('Transcribe videos'), resources ('from 1000+ platforms or local video files'), and implementation details ('using OpenAI Whisper'). It distinguishes this tool from its siblings (check_dependencies, list_supported_sites, list_transcripts) by focusing on the core transcription functionality rather than dependency checking, site listing, or transcript listing.

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 clear context about when to use this tool: for transcribing videos from numerous platforms or local files. It doesn't explicitly state when NOT to use it or name specific alternatives, but the sibling tools are clearly for different purposes (checking dependencies, listing sites, listing transcripts), so the usage context is well-defined.

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