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

Annotations only cover readOnlyHint=false and destructiveHint=false, so the description carries the load and does so well: it discloses BACKGROUND execution, an HTTP 202 + job_id return, the polling contract via lab_get_job, and two failure modes (400 on empty timeline, 503 when GEMINI_API_KEY is missing). This is exactly the operational 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?

Front-loaded with the core action and drift rationale before the job/refusal details. It is dense but each sentence (background behavior, polling, refusals) earns its place; slightly long but not padded.

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?

With no output schema, the description steps in to explain the return value (job_id, findings in the job result) and the polling path, and it pre-empts the two refusals an agent would otherwise waste time on. Nothing needed to call it 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% and the schema already documents each parameter in depth, so the baseline is 3. The description echoes check_references and implies model can be omitted, but adds little meaning beyond what the schema strings already provide.

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 action ('start the continuity pass over a sequence') and precisely scopes what it does: 'every shot is compared against its PREDECESSOR and, with check_references, against the character and location reference boards.' The drift-catching framing ('the flat that changed between two shots') makes its distinct purpose legible against siblings.

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 clear when-to-use context ('the pass that catches drift ... the actual enemy in AI film, not the cut') and prerequisites ('add shots with lab_add_clip first'), plus the check_references cheaper-pass alternative. It routes the agent to lab_get_job for polling but does not explicitly contrast against sibling review/analysis tools, so it stops short of full when-not guidance.

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