get_transcript

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

With no annotations, the description discloses important behavioral traits: the result distinguishes between 'captions definitively do not exist' and 'transcribing audio would still work' via the aiFallback object. It also reveals that ai_fallback starts an async job costing 1 credit and taking 1-3 minutes. This goes well beyond a simple 'get transcript' statement and helps the agent anticipate edge cases.

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 a single dense paragraph that front-loads the purpose and then details formats and fallback behavior. It is slightly redundant with the schema but remains concise for the amount of context it provides.

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 lacking an output schema, the description explains key result fields (captionsUnavailable, available) and the async fallback process, which covers the main edge cases. It does not describe the full transcript structure, but for a two-parameter tool this is reasonable. The absence of annotations is compensated by the description's rich behavioral detail.

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 already describes both parameters thoroughly (video formats, ai_fallback behavior, cost, timing). The description largely restates this information without adding new parameter-level meaning. Baseline is 3 due to 100% schema coverage, and this description does not elevate it.

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 identifies the tool's function ('Fetch the full transcript for a video') and lists accepted input formats (YouTube ID/URL, TikTok, Instagram, X, Facebook, direct media URLs). This distinguishes it from sibling tools like search_videos or list_channel_videos, which focus on discovery rather than content retrieval.

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?

Provides explicit usage guidance for the fallback flow: if no transcript returns and aiFallback.available is true, call the tool again with ai_fallback: true. It does not explicitly compare to alternative tools, but the description makes the primary use case clear and the fallback condition is actionable.

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