transcribe_video

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: a 10-60 second latency window and the caveat that word-level timestamps are returned only 'when the API supports them,' which warns the agent about conditional output.

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 tight sentences with zero filler. The core action is front-loaded, and the return content plus latency caveat follow in order of importance.

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?

An output schema exists, so return-value structure need not be re-explained; annotations carry the safety semantics; and the description still supplies latency expectations and the conditional-timestamp caveat. Nothing essential for correct invocation is missing.

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 100%, so both parameters (video_url, language) are already fully documented in the schema, including accepted URL forms and the ISO-639-1 pattern. The description adds no additional parameter meaning, so the baseline 3 applies.

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?

States a specific verb and resource ('Transcribe a TikTok video's speech') and names the mechanism (server's speech-to-text API). No sibling tool (get_profile, get_videos, get_comments, search_videos, discover_creators) performs transcription, so the tool is unambiguously distinguishable.

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 rather than stated: an agent can infer it should call this when it needs spoken-word text from a video. There is no explicit when-to-use/when-not guidance, no alternative named, and no preconditions (e.g., public video, language availability) spelled out.

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