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Quantum Expectations

Hardware Gate-Cycle Timings

list_hardware_timings
Read-onlyIdempotent

Return per-platform gate-cycle timings (2Q gate time, readout time, in SI seconds) plus the representative device and native 2Q gate name, with source URLs. Joins list_current_quantum_computers via hardwareType. Use for runtime estimates, ratio analysis, or as inputs to compute_quantum_volume_rate. Values are representative current-generation numbers, not records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds behaviorally meaningful context beyond annotations: that timings include representative current-generation numbers rather than historical records, that results include source URLs, and that the data is sourced through a join on hardwareType. This adds useful caveats not captured in the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact at three sentences, front-loaded with the output content and its units. Every sentence provides necessary detail: what is returned, how it relates to sibling tools, and a caution about the representative nature. It could be slightly tighter, but it is not verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Without an output schema, the description reasonably covers return fields: 2Q gate time, readout time, SI seconds, representative device, native 2Q gate name, and source URLs. It also explains provenance and intended use. Minor gaps remain, such as not describing what a typical response entry looks like or edge cases for missing timings, but overall it is adequately complete for the tool's purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema leaves no semantics to clarify. Per rubric this is a baseline 4: the description cannot add parameter meaning if there are none, and it does not need to compensate since the tool takes no input.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Return') and clearly states the resource: per-platform gate-cycle timings including exact fields (2Q gate time, readout time, device, gate name, source URLs). It differentiates itself from siblings by explaining the join with list_current_quantum_computers and explicitly targeting compute_quantum_volume_rate as a downstream consumer.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: 'Use for runtime estimates, ratio analysis, or as inputs to compute_quantum_volume_rate.' It implies when to use this tool but does not explicitly state when not to use it or mention a specific alternative tool, so it misses the full when/when-not structure for a 5.

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

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TDQS

A4.4/5.0
Disambiguation5/5

Every tool has a clearly distinct role: compute_expectation and compute_required_error_rate are forward/inverse pairs, compare_hardware_scenarios is a batch wrapper for compute_expectation, and the list_* and get_* tools each target a different data category (hardware, timing, historic, examples, codes). The fit_historic_series tool is distinct from get_historic_series (analysis vs. retrieval). No two tools appear ambiguous.

Naming Consistency5/5

All tool names follow a strict lower_snake_case verb_noun pattern: compute_*, get_*, list_*, fit_*, compare_*. The verbs precisely indicate the action (computation, retrieval, fitting, comparison) and are used consistently across the set.

Tool Count5/5

With 12 tools, the server is well within the ideal 3-15 range. Each tool serves a distinct purpose in the quantum resource estimation workflow: data listing, forward/inverse expectation calculations, fault-tolerant resource estimation, rate computation, historic analysis, and context retrieval. No tool feels redundant or unnecessary.

Completeness5/5

The tool surface comprehensively covers the domain: current hardware data (list_current_quantum_computers, list_hardware_timings), historical trends (get_historic_series, fit_historic_series), algorithm resource examples (list_example_algorithms), error correction codes (list_qldpc_codes), forward and inverse error calculations (compute_expectation, compute_required_error_rate), batch comparison (compare_hardware_scenarios), deep resource estimation (compute_fault_tolerant_resources), a throughput metric (compute_quantum_volume_rate), and the agent brief. There are no obvious missing operations for the stated purpose.

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