Quantum Expectations

Measured QUOPS Capability Scores

list_quops_scores

Read-onlyIdempotent

Return the measured QUOPS (quantum universal operation performance system, a cross-platform capability benchmark) scores (arXiv:2609.12146): per device, the largest random universal circuit size executed at polarization >= 1/sqrt(e) inside the cone w^2 <= s <= w^3, with width, QUOPS rate, architecture (physical, physical-postselected, logical) and source URL, plus the utility-scale targets in the same unit (RSA-2048 and FeMoco). These are measurements, the yardstick the site's own model is checked against: compare them with modelCapability.quopsEquivalent on the compute_expectation hardware context. Vendor and device names appear here because this table is agent-facing only.

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`scores`	Yes
`targets`	Yes
`definition`	Yes
`admissibleCone`	Yes
`polarizationThreshold`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 23, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "admissibleCone": {},
+    "definition": {
+      "type": "string"
+    },
+    "polarizationThreshold": {
+      "type": "number"
+    },
+    "scores": {
+      "items": {
+        "additionalProperties": {},
+        "properties": {
+          "architecture": {
+            "enum": [
+              "physical",
+              "physical-postselected",
+              "logical"
+            ],
+            "type": "string"
+          },
+          "code": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "device": {
+            "type": "string"
+          },
+          "discardFraction": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "hardwareType": {
+            "type": "string"
+          },
+          "id": {
+            "type": "string"
+          },
+          "physicalQubits": {
+            "maximum": 9007199254740991,
+            "minimum": -9007199254740991,
+            "type": "integer"
+          },
+          "quopsRatePerSecond": {
+            "type": "number"
+          },
+          "quopsScore": {
+            "type": "number"
+          },
+          "source": {
+            "format": "uri",
+            "type": "string"
+          },
+          "vendor": {
+            "type": "string"
+          },
+          "width": {
+            "type": "number"
+          },
+          "year": {
+            "type": "number"
+          }
+        },
+        "required": [
+          "id",
+          "device",
+          "vendor",
+          "hardwareType",
+          "physicalQubits",
+          "architecture",
+          "code",
+          "quopsScore",
+          "width",
+          "quopsRatePerSecond",
+          "discardFraction",
+          "year",
+          "source"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "targets": {
+      "items": {
+        "additionalProperties": {},
+        "properties": {
+          "id": {
+            "type": "string"
+          },
+          "logicalQubits": {
+            "type": "number"
+          },
+          "note": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "problem": {
+            "type": "string"
+          },
+          "quopsRateTargetPerSecond": {
+            "type": "number"
+          },
+          "quopsTarget": {
+            "type": "number"
+          },
+          "resourceEstimateSource": {
+            "format": "uri",
+            "type": "string"
+          },
+          "source": {
+            "format": "uri",
+            "type": "string"
+          },
+          "timeBudget": {
+            "type": "string"
+          },
+          "toffoliCount": {
+            "type": "number"
+          }
+        },
+        "required": [
+          "id",
+          "problem",
+          "logicalQubits",
+          "toffoliCount",
+          "quopsTarget",
+          "quopsRateTargetPerSecond",
+          "timeBudget",
+          "resourceEstimateSource",
+          "source",
+          "note"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "definition",
+    "polarizationThreshold",
+    "admissibleCone",
+    "scores",
+    "targets"
+  ],
+  "type": "object"
+}

AddedSep 16, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered. The description adds useful context beyond that: this is a static measurement table, returns include architecture tier and source URL, and vendor/device names appear because the table is agent-facing only. It does not mention caching or refresh cadence, but with annotations doing the heavy lifting this is solid.

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?

Front-loads purpose and the acronym expansion, then the definition, then the comparison target. Every clause carries information, but the paragraph is dense with nested parentheticals, inline math, and the arXiv id packed into one block, which slightly hurts scannability.

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

Completeness5/5

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

An output schema exists, so return-field enumeration is not required, yet the description still names the key fields (width, QUOPS rate, architecture tiers, source URL) and the reference targets in the same unit. Combined with annotations covering safety, an agent has everything needed to call it correctly.

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 takes zero parameters, so parameter semantics are moot and the baseline of 4 applies. The description correctly describes what is returned rather than implying any filtering inputs.

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?

States a specific verb ('Return') and a precisely defined resource (measured QUOPS scores, with the acronym expanded and an arXiv citation), and explicitly contrasts measurements with the site's own model, distinguishing it from model-based siblings. An agent can tell this is the ground-truth benchmark table, not a computation.

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?

Gives explicit usage direction: compare with modelCapability.quopsEquivalent in the compute_expectation hardware context. That routes the agent to the right sibling for the downstream comparison. It stops short of stating when-not to use it or naming alternative data sources.

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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