Privi Quantum

Privi Car: best route for a list of stops

car_route

Order the stops for the shortest trip. The exact best order is proven classically (Held-Karp); with five stops or fewer the same problem also runs as a QUBO on the CVaR-QAOA quantum simulator, and the signed receipt shows both. Returns the order, distance, and how much it saves over the order given. Uses straight-line distance unless you pass distances_km. Stops are not stored.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "stops": "<stops>"
    },
    "name": "car_route"
  }
}

Input Schema

Name	Required	Description
`stops`	Yes	2-12 stops as {name, lat, lon}; the first is the start
`round_trip`	No	Return to the start at the end (default true)
`distances_km`	No	Optional n x n road distances or minutes; overrides straight-line distance

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 13, 2026

TDQS

A3.7/5.0

Behavior4/5

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

With annotations present but sparse, the description adds real substance: the exactness guarantee (Held-Karp), the alternate QUBO/CVaR-QAOA execution path for five stops or fewer with a signed receipt of both, the distance model default, and the fact that stops are not stored. It stops short of disclosing latency, whether the quantum path changes results, or how the receipt is verified, so it is strong but not exhaustive.

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-loaded with the action and result, then supporting detail. Four sentences with little waste; the Held-Karp/QUBO sentence is dense but earns its place by explaining the signed receipt, which is otherwise unexplained output.

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?

No output schema exists, and the description compensates by naming the return values (order, distance, savings over the given order). Combined with the distance-model note and the 'stops are not stored' statement, an agent has enough to call it correctly; only the nature and verification of the signed receipt remain vague.

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

Parameters3/5

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

Schema coverage is 100%, so the baseline is 3. The description restates the stops bound and clarifies that distances_km overrides straight-line distance, which is mildly useful framing, but it adds no syntax, units, or shape detail (n x n matrix, road distance vs minutes) beyond what the schema already documents.

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

Purpose4/5

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

States a specific verb and resource: 'Order the stops for the shortest trip', plus what it returns (order, distance, savings). An agent can immediately tell this is a route-optimization tool, distinct from the key/fleet/history siblings, though it never names a sibling or explicitly contrasts itself with one.

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

Usage Guidelines3/5

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

Usage is only implied: you call it when you have a list of stops and want an optimal ordering, and the 2-12 stop bound is stated in the schema. There is no explicit when-not guidance, no mention of when to prefer a plain distance lookup, and no statement of prerequisites or cost, so an agent must infer the selection conditions.

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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