Collect a lab-results analysis started with start_lab_analysis

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

Annotations already declare readOnly, idempotent, non-destructive, and openWorld, so the safety profile is covered; the description goes further by enumerating the four possible states and disclosing the 30-minute retention window for expired results. It stops short of describing what a failed response contains, which matters since no output schema exists.

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?

Two tight sentences, zero filler, with the identity of the returned job result and the status semantics front-loaded. Every clause (polling cadence, payload fields, retention window) carries distinct operational value.

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 correctly carries the burden of naming the return shape for the done state (health_picture, recommendations) and the full status taxonomy. The gap is the failed-state payload and the unresolved overlap with the get_job_result sibling.

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 single job_id parameter is fully documented in the schema as the value returned by start_lab_analysis. The description's "Takes only the job_id" restates that without adding format, validation, or reuse semantics, so the 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 resource ("Returns the result of a start_lab_analysis job") and explicitly anchors the tool to its producer sibling, start_lab_analysis. An agent can distinguish it from the start tool or explain_my_lab_results without opening the schema.

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 concrete polling guidance: pending means call again in a few seconds, and expiry after 30 minutes sets a deadline for retrieval. It does not address when to use this versus the sibling get_job_result, which could be a competing way to fetch job output.

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