Solve

Solve

curl --request POST \
  --url https://win.oneshotagent.com/v1/tools/solve

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://win.oneshotagent.com/v1/tools/solve",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://win.oneshotagent.com/v1/tools/solve"

	req, _ := http.NewRequest("POST", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://win.oneshotagent.com/v1/tools/solve")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)

response = http.request(request)
puts response.read_body

POST

tools

solve

Solve

curl --request POST \
  --url https://win.oneshotagent.com/v1/tools/solve

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://win.oneshotagent.com/v1/tools/solve",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://win.oneshotagent.com/v1/tools/solve"

	req, _ := http.NewRequest("POST", url, nil)

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

require 'uri'
require 'net/http'

url = URI("https://win.oneshotagent.com/v1/tools/solve")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)

response = http.request(request)
puts response.read_body

Routing, allocation, packing and scheduling are supported.

Quote and job lifecycle

The first request returns HTTP 402 with a quoted price. Retry identical input with X-Quote-ID, payment and an Idempotency-Key; HTTP 202 returns a request_id to poll at GET /v1/requests/:id. Same key and input return the original job. SDKs (agent.solve, client.solve/asolve) handle quoting, payment and polling (420-second timeout); MCP, LangChain and GAME expose oneshot_solve, GAME with JSON-text blocks.

Routing

Minimise distance, time, or vehicles then distance over vehicles, stops and coordinates or ids-ordered square matrices. Optional demand, service times, windows and shifts constrain routes; every stop is served. Defaults: kilometres, minutes, 40 units/hour. Input:

{
  "problem": "routing",
  "time_limit_s": 30,
  "routing": {
    "objective": "distance",
    "vehicles": [{ "id": "van", "capacity": 10, "start": { "id": "depot" } }],
    "stops": [{ "id": "delivery", "demand": 1, "location": { "id": "delivery" } }],
    "matrix": {
      "ids": ["depot", "delivery"],
      "distance": [[0, 1], [1, 0]],
      "time": [[0, 1], [1, 0]]
    }
  }
}

Example result:

{
  "status": "feasible",
  "objective_value": 2,
  "bound": null,
  "gap": null,
  "solution": {
    "routes": [{
      "vehicle": "van",
      "stops": [{ "id": "delivery", "arrival": 1, "departure": 1, "load_after": 1 }],
      "distance": 2,
      "time": 2
    }],
    "unserved": []
  },
  "checks": [
    { "name": "every_stop_once", "satisfied": true, "worst_violation": 0, "detail": "" },
    { "name": "vehicle_capacity", "satisfied": true, "worst_violation": 0, "detail": "" },
    { "name": "stop_windows", "satisfied": true, "worst_violation": 0, "detail": "" },
    { "name": "shift_windows", "satisfied": true, "worst_violation": 0, "detail": "" },
    { "name": "route_continuity", "satisfied": true, "worst_violation": 0, "detail": "" },
    { "name": "objective", "satisfied": true, "worst_violation": 0, "detail": "" }
  ],
  "conflicts": [],
  "meta": {
    "problem": "routing",
    "size": { "stops": 1, "vehicles": 1 },
    "variables_estimated": 12,
    "variables_built": 12,
    "solve_time_s": 0.1,
    "time_limit_s": 30,
    "conflicts_complete": null
  }
}

Allocation

Assign items (quantity default 1) to options (optional capacity) using pairs (per-unit cost/value). Optional: split, max_total_cost, min_share/max_share (if_used floors), required, forbidden. maximise_value may leave items unassigned; with shares or a budget, largest/smallest lot ratio ≤1,000,000 (bad_quantity before payment).

{
  "problem": "allocation",
  "allocation": {
    "objective": "minimise_cost",
    "items": [{ "id": "L1", "quantity": 120 }, { "id": "L2", "quantity": 80 }, { "id": "L3", "quantity": 100 }],
    "options": [{ "id": "C1", "capacity": 200 }, { "id": "C2", "capacity": 150 }],
    "pairs": [
      { "item": "L1", "option": "C1", "cost": 1.9 }, { "item": "L1", "option": "C2", "cost": 2.1 },
      { "item": "L2", "option": "C1", "cost": 2.4 }, { "item": "L2", "option": "C2", "cost": 2.0 },
      { "item": "L3", "option": "C1", "cost": 1.7 }
    ],
    "min_share": [{ "option": "C2", "share": 0.25 }]
  }
}

Packing

Size/capacity keys match dimensions. Quantities: default 1, maximum 1,000,000. bin minimises bins; knapsack maximises nonnegative values using one bin. incompatible pairs forbid sharing; equal IDs return contradictory_input before quoting. No geometric placement.

{
  "problem": "packing",
  "packing": {
    "variant": "bin",
    "dimensions": ["weight"],
    "bins": [{ "id": "box", "capacity": { "weight": 10 }, "quantity": 3 }],
    "items": [
      { "id": "A", "size": { "weight": 5 }, "quantity": 2 },
      { "id": "B", "size": { "weight": 4 }, "quantity": 2 },
      { "id": "C", "size": { "weight": 1 }, "quantity": 2 }
    ]
  }
}

Result: two bins, status: "optimal", gap: 0; a knapsack solution adds left_out: [{id,count}]:

{
  "bins": [
    { "bin": "box", "index": 0, "items": [{ "id": "A", "count": 2 }], "used": { "weight": 10 } },
    { "bin": "box", "index": 1, "items": [{ "id": "B", "count": 2 }, { "id": "C", "count": 2 }], "used": { "weight": 10 } }
  ]
}

Schedule

Jobs carry integer duration, optional release, due, per-resource needs and weight; resources carry capacity, optional calendar windows and cost_per_unit_time; precedence makes after start lag after before ends. Times are integers in time_unit (default minutes); jobs fit one calendar window. Objectives: makespan; tardiness (weighted lateness past due, else a hard deadline); cost (weight × duration × held needs at their rate). Input and solution:

{"problem":"schedule","schedule":{"objective":"makespan","resources":[{"id":"machines","capacity":2}],"jobs":[{"id":"job","duration":10,"needs":{"machines":1}}]}}

{"starts":[{"job":"job","start":0,"end":10,"resources":{"machines":1},"tardiness":0}],"makespan":10}

Status, checks and conflicts

Result status	Meaning
`optimal`	Proven optimum; never for routing.
`feasible`	Checked solution without proven optimality.
`infeasible`	Proven contradiction; solution/objective/bound/gap null, checks empty.
`timeout`	Time elapsed; may carry a checked solution; charged regardless.

Every field is present; routing bound/gap are null. Objectives are recomputed independently; without a solution, objective null, checks empty. checks[] (name, satisfied, worst_violation in input units, detail) all pass, or the job fails with internal_error. conflicts[] (infeasible only): constraints[] (family, ref, label) plus explanation, not necessarily minimal; meta.conflicts_complete reports completeness.

Limits

500 stops; integer time_limit_s 1–300, default 30; quantities finite, nonnegative, at most 1e12; at most 100,000 estimated variables:

routing:    4 * (stops + 2 * vehicles)
allocation: 2 * pairs + options + items
packing:    bins * (item kinds + 1)    for bin;  item kinds    for knapsack
schedule:   jobs * (3 + resources) + precedence + calendar windows + horizon

Pricing size: allocation items × options; packing kinds × bins × dimensions; else the estimate. Unsupported numeric precision/magnitudes fail before payment. Unknown fields, duplicate/empty/unknown IDs, reversed/overlapping windows, malformed matrices, contradictory pairs and precedence cycles fail before payment: HTTP 400, error: "invalid_input", named code and message.

Overview

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Quote and job lifecycle

Routing

Allocation

Packing

Schedule

Status, checks and conflicts

Limits

​Quote and job lifecycle

​Routing

​Allocation

​Packing

​Schedule

​Status, checks and conflicts

​Limits

Quote and job lifecycle

Routing

Allocation

Packing

Schedule

Status, checks and conflicts

Limits