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

The description discloses a critical side effect absent from annotations: 'SPENDS THE ACCOUNT'S LLM CREDITS — every message is billed against them.' It also reveals stateful behavior (conversation_id for continuation) and auth requirements, adding substantial context beyond the annotation flags.

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 concise sentences, front-loaded with purpose and the billing warning. Every sentence carries a distinct operational fact: purpose, cost, when to use, continuation, and auth. No filler or redundancy.

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?

The description covers purpose, cost, usage guidance, continuation, and auth, which is strong for a tool without an output schema. It could mention behavior for invalid or incomplete transcription IDs, but the schema's 'completed transcription id' plus 'get an answer' gives an agent enough to invoke 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 description coverage is 100%, so the schema already documents all three parameters clearly. The description reinforces conversation_id's role ('Pass back the returned conversation_id') but adds no meaningful parameter-level detail beyond what the schema provides.

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: 'Ask a question about an existing transcript and get an answer from the model, with the transcript as context.' This clearly distinguishes it from sibling tools like transcribe_upload, search_transcripts, or export_transcript. The title 'Chat with a transcript' reinforces the function.

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?

Explicitly gives a when-not-to-use condition: 'If you already hold the transcript text, answering directly is cheaper and usually just as good; this is for when you do not.' It also explains how to continue a thread by passing back conversation_id, and notes the OAuth 2.1 token requirement.

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