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

Annotations cover safety (readOnlyHint=false, destructiveHint=false, openWorldHint=true), and the description layers on what they don't say: it is asynchronous (returns a job id immediately), it costs video credits billed at queue time, it needs an API key, and it requires a StartupHub.ai account. Cost and auth disclosure beyond annotations is exactly the value-add expected here.

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?

Five short sentences, each carrying distinct information (capability, inputs, async return, follow-up, cost/auth). Front-loaded with the outcome and free of filler.

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?

No output schema exists, and the description compensates by explaining the return contract (job id, then mp4_url via get_article_video) plus the billing/auth preconditions. Nothing an agent needs to invoke and follow through 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 every parameter including the format enum and defaults is already documented structurally. The description only echoes the url/text mutual exclusivity that the schema already states, adding no new parameter detail. 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 dual resource ('Turn an article URL, or a block of text, into a narrated video with captions'), so the agent knows exactly what comes out. It also implicitly separates itself from the sibling get_article_video, which it names as the polling counterpart.

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 an explicit end-to-end workflow: call this, capture the job id, then poll get_article_video until status is done, then use mp4_url. The condition selecting the follow-up tool is spelled out rather than left to inference.

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