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

The description discloses the asynchronous nature, credit charging, automatic refund on failure, up-front rejection without charge, and attachment to get_post responses — all side effects not visible in the sparse annotations. It does not contradict the annotations; readOnlyHint=false is consistent with a queueing, credit-consuming operation.

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 sentences, each adding a distinct fact: what it does, accepted inputs, async behavior/result location, credit/refund policy, and excluded inputs with the correct alternative. The most important identifying behavior is front-loaded.

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 a two-parameter async tool with no output schema, the description covers invocation inputs, workflow, cost consequences, failure refunds, and unsupported cases. No additional information is needed for an agent to select and call it correctly.

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 coverage is 100%, and the schema already explains that url is an alternative to postId and that postId is the internal post id. The description restates this as 'a public post URL or an internal post id' without adding format, precedence, or required-value details, so it adds little beyond the schema.

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 names a specific action ('Queues AI transcription of the spoken audio for a video post') and a clear resource, while distinguishing it from the sibling request_visual_analysis. It also clarifies accepted input forms, leaving no ambiguity about what the tool does.

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 explicitly states when the tool is appropriate (video posts with spoken audio) and when it is not (image slideshows and photo posts), and names the alternative request_visual_analysis for the excluded cases. The async workflow is also prescribed with get_job_status, so an agent knows exactly how to consume the result.

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