list_transcript_languages

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

With no annotations, the description helpfully enumerates the shape of what the tool returns: human-written vs auto-generated captions and translatable languages. It could add a note about read-only behavior or missing captions, but the single verb 'List' makes the non-mutating nature reasonably clear.

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?

Two sentences, no filler. The first sentence front-loads the exact output categories, the second provides actionable selection guidance by referencing get_transcript.

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 listing/discovery tool, the description covers what data to expect and when to call it, which is enough for an agent to use it correctly. It does not specify auth requirements or behavior when no captions exist, but those are secondary for this 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?

The schema already describes the only parameter ('Video ID or URL') with 100% coverage, so the description does not need to add parameter-level detail. No extra semantic guidance is provided, which is acceptable at the baseline.

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 what the tool does: lists available caption tracks (language, human-written vs auto-generated, translatable) and the languages YouTube can machine-translate into. It is unambiguous and distinct from transcript-fetching or metadata tools.

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?

Explicitly tells the agent when to use this tool—'Use before get_transcript when unsure'—and names the relevant sibling tool, which is the main decision it needs to make.

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