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

Beyond the annotations (readOnly=false, idempotent=false, openWorld=true), the description discloses genuinely useful behavior: it spends the account's Google usage, occupies a maxJobs slot, and waits only ~50 s before returning a jobid rather than the finished artifact. These cost, concurrency, and async-timing facts are exactly the kind of context annotations cannot express.

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?

Purpose is front-loaded in the first sentence and the content is packed into a few semicolon-separated clauses with little filler. It is dense and slightly run-on (mixing artifact types, the job model, waiting, cost, and routing in one breath), but no sentence is wasted.

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 19-parameter async generator with no output schema, the description is unusually complete: it covers the job model, the ~50 s wait, jobid continuation, and even what a finished job yields (artifact id, download URLs, text or JSON). Only edge cases (failures, retries, cancel semantics) are left to siblings like notebook_cancel_job and notebook_retry_artifact.

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%, so every one of the 19 parameters already carries its own description, including enum values and per-type applicability. The description adds only the generic line 'Options apply per type (see each option)', which restates what the schema already encodes, so the baseline 3 is warranted.

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 gives a precise verb and resource and enumerates all ten artifact types it can produce (audio, video, report, table, quiz, etc.), so an agent knows exactly what it generates. It also distinguishes itself as asynchronous ('as a job'). It stops short of naming the nearest sibling, notebook_generate_suggested_item, whose quiz/flashcards/mindmap overlap leaves a small ambiguity.

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 clearly explains the two modes ('With notebook' vs 'One-shot: without notebook, a new notebook is made from urls and/or text') and prescribes the follow-up path (continue with notebook_get_job (wait: true)). That is strong when-to-use guidance, though it never explicitly rules out or routes to the overlapping sibling generate_suggested_item.

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