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

With annotations already covering safety hints, the description adds substantial behavioral context: exact credit pricing, added transcription cost for video-only input, ~40 s wait before polling get_job, platform-specific output norms, language default, and YouTube chapter timing rules. This is far beyond what the annotations provide.

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 dense and information-rich, with most critical constraints stated up front and no obvious filler. However, it is a long single paragraph and leads with pricing rather than the core action, which slightly reduces scanability.

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 an 11-parameter paid async tool with no output schema, the description provides unusually complete context: result shape, chapter constraints, platform behavior, language default, and polling guidance. It still leaves out maxCredits, quoteOnly, and durationSeconds behavior, which matter for cost control and previewing.

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 low at 36%, and the description compensates well for the core inputs: transcriptionJobId job types, subtitles, fileId/mediaUrl, platforms and defaults, language behavior, titleCount range/default, and context notes. It still omits meaningful detail for maxCredits, quoteOnly, and durationSeconds, so coverage is strong but incomplete.

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 states a specific verb and resource: writes publishing metadata (titles, description, hashtags, YouTube chapters) from what is said in a video. It distinguishes this from transcription by saying no re-transcription is needed when a transcript exists, and it clearly defines the generated artifacts per platform.

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?

It gives clear input-selection guidance: pass transcriptionJobId or subtitles, otherwise fileId or mediaUrl, and for trimmed videos use the trim job so chapter times match. It also explains the async wait/poll fallback. It lacks explicit when-not guidance and does not mention cost-checking siblings like quote or plan.

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