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

Goes well beyond the annotations: it discloses that summarization triggers transcription as a side effect, that the call can return a still-running jobId rather than a summary, and it spells out quota behavior (a few per day on free accounts, unlimited with credits). That explains the non-readOnlyHint semantics and rate limits, which annotations alone would not.

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?

Front-loaded with the value proposition and output shape, then the failure path, then limits – a sensible order with no filler. The final sentence packs both the still-running job semantics and the quota rules into one dense statement, which slightly crowds the async guidance into a parenthetical.

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?

There is no output schema, yet the description fully specifies the return content (TL;DR plus key points with timestamps) and the asynchronous failure mode with its recovery path. For a two-parameter tool with rich annotations, nothing an agent needs in order to call or retry correctly 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 the url and ai parameters are already fully documented, including supported platforms and the ai flag's dependency on list_my_transcripts or get_my_transcript. The description adds no syntax or format detail beyond the schema, 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 ('Get a short AI summary of a public video') and pins down the exact return shape: a 2-3 sentence TL;DR plus 3-8 timestamped key points. It also implicitly separates itself from get_transcript by citing the same cost/wait profile, so an agent can tell what it is getting 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?

Gives clear operational guidance for the non-happy path: if transcribing is still running, call transcribe_status and then re-call summarize_video. It does not explicitly say when to prefer this over siblings like ask_video or get_transcript, which leaves the main routing decision to inference, but the in-flow retry instruction is concrete.

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