transcribe_youtube

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

With no annotations provided, the description carries the full burden, and it does meaningful work: it discloses the processing pipeline (audio download, silence-based chunking under 25MB), the transcription backend, verbatim output with timestamps, and that two files are written. It omits operational details such as required Groq credentials, expected runtime for long videos, and failure behavior on unavailable or region-locked videos, which keeps it below a 5.

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 first sentence front-loads the whole pipeline, and the Args section is compact and scannable with one entry per parameter. It is slightly heavy in the opening clause (silence-detected chunking, <25MB, model name) but no sentence is wasted 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?

For a multi-step media tool with an output schema already documenting return values, the definition covers inputs, default locations, and output artifact types. The main remaining gaps are credential requirements and runtime/size expectations for long videos, which an agent would want before invoking a download-and-transcribe job.

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 0%, so the description must compensate, and the Args block covers all three parameters: the accepted URL forms for url, the default path pattern and emitted file types for output_path, and the auto-detect fallback for language. It stops short of naming the exact language code format beyond examples, but the added meaning is substantial versus a bare schema.

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 gives a specific verb chain and resource: download audio, chunk it, transcribe verbatim with Groq Whisper Large V3, emitting timestamped segments. That is clearly distinct from siblings like extract_keyframe, get_video_info, list_channel_videos, and check_groq_quota, so an agent can identify the right tool without opening the schema.

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?

Usage is implied by the task described (give a URL, get a transcript), but there is no explicit statement of when to reach for this versus get_video_info or list_channel_videos, and no exclusions or prerequisites such as API key or quota checks. The .md and _raw.json outputs hint at the intended scope, but a routing hint to check_groq_quota or get_video_info would push this higher.

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