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

Annotations already classify the tool as read-only and idempotent, and the description adds meaningful behavioral context beyond that: it discloses that the data are best-case demonstrations, that the joined device run orders of magnitude slower, and that the results include source URLs. This is important caveat information an agent could not infer from the schema or annotations.

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?

The description is four sentences with each sentence earning its place: what is returned, the key caveat, the intended use cases, and the instruction to say so when quoting a runtime. It is dense but not verbose, and the most important caveat is front-loaded.

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?

There is no output schema, so the description needs to explain return values and semantics, which it does thoroughly: gate-cycle timings in SI seconds, representativeDevice, native 2Q gate name, source URLs, and the testbed provenance caveat. The description is self-contained and leaves no important ambiguity for an agent deciding whether or how to call it.

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?

The input schema is empty (0 parameters) and schema description coverage is 100%, so there is no parameter semantics gap for the description to fill. The baseline for a zero-parameter tool is high, and no further parameter-level detail is needed.

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 opens with 'Return per-platform gate-cycle timings', immediately identifying the specific resource and the exact fields returned (2Q gate time, readout time, representativeDevice, native 2Q gate name, source URLs). It also explains the join to list_current_quantum_computers, which helps distinguish this retrieval tool from the compute_* and list_* 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?

The description explicitly states when to use the tool: 'Use for ratio analysis or as optimistic lower-bound inputs to runtime estimates and compute_quantum_volume_rate'. It also gives a clear warning that the numbers are 'BEST-CASE DEMONSTRATIONS from small testbeds' rather than measurements on the joined devices, so an agent knows not to present them as actual device performance.

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