Warm up a model

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

Annotations already declare readOnly=true, idempotent=true, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely new behavioral context that annotations cannot express: the call is fire-and-forget, it exists to mask a one-to-two minute cold-start latency, and it should be overlapped with other work. It stops short of stating what happens if the model is already warm or what the response confirms, which keeps it below a 5.

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 sentences, both front-loaded with the action and the model-value mapping before the rationale. No filler, though the second sentence's clause buries the strongest usage instruction ("call this as soon as you know") after the latency explanation.

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 single-parameter, zero-required, idempotent pre-load tool with a full output schema and rich annotations, the description supplies exactly the missing piece: when to fire it and how to overlap it with other work. Nothing an agent needs in order to invoke it correctly is absent.

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 enum is self-documenting, so the baseline is 3. The description earns above baseline by tying each value to the downstream tool that benefits from the warm-up (sam/medsam → segment_objects, nuclei → detect_nuclei), which tells the agent how to pick a value from intent rather than from the string alone. It is marginally less complete than the schema, which also mentions classify_cells for 'nuclei'.

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 — "Start loading a model ahead of use, without waiting for it" — and immediately maps each model value to the sibling operation that will consume it (segment_objects, detect_nuclei). An agent can distinguish this pre-loading tool from the actual segmentation/detection tools without opening either 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 an explicit trigger ("call this as soon as you know you will need it (for example right after uploading)") and an explicit behavioral instruction for the interim ("do other work meanwhile"). It also justifies the advice with the condition that motivates it — a quiet spell causing a one-to-two minute cold start.

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