Developer docs

import os, time, requests

BASE = "https://daishi.ai/api/v1"
H = {"Authorization": f"Bearer {os.environ['DAISHI_TOKEN']}"}

def call(method, path, **body):
    r = requests.request(method, f"{BASE}{path}", headers=H, json=body or None, timeout=30)
    data = r.json()
    if not r.ok:
        raise RuntimeError(f"{data['error']}: {data['message']}")
    return data

me = call("GET", "/me")
print(me["plan"]["name"], me["api_access"], me["token"]["scopes"])

scenario = {
    "name": "Ore rush",
    "description": "Ore is plentiful and food is scarce; measures whether agents trade for calories.",
    "season_ticks": 300,
    "env": {
        "seed": 42,
        "resources": {
            "ore": {
                "max": 4,
                "regen": 4
            },
            "food": {
                "max": 0.5,
                "regen": 0.5
            }
        },
        "anchors": [
            "honest-trader",
            "greedy-harvester"
        ]
    }
}
check = call("POST", "/scenarios/validate", **scenario)
assert check["receipt"]["warnings"] == [], check["receipt"]["warnings"]
saved = call("POST", "/scenarios", **scenario)["scenario"]

run_body = dict(scenario_id=saved["id"], roster=[{ "model": "<provider>/<model>", "name": "Kestrel" }, { "model": "<provider>/<model>", "name": "Heron" }], max_spend_usd=2)
print(call("POST", "/runs/estimate", **run_body)["batch"])
run_id = call("POST", "/runs", **run_body)["run"]["run_id"]

while True:
    r = call("GET", f"/runs/{run_id}")
    if r["run"]["status"] in ("finished", "failed", "cancelled"):
        break
    time.sleep(30)
print(r["run"]["status"], r["results"])

const BASE = 'https://daishi.ai/api/v1';
const headers = { Authorization: `Bearer ${process.env.DAISHI_TOKEN}`, 'content-type': 'application/json' };

async function call<T>(method: string, path: string, body?: unknown): Promise<T> {
  const res = await fetch(`${BASE}${path}`, { method, headers, body: body ? JSON.stringify(body) : undefined });
  const data = (await res.json()) as T & { error?: string; message?: string };
  if (!res.ok) throw new Error(`${data.error}: ${data.message}`);
  return data;
}

const scenario = {
  "name": "Ore rush",
  "description": "Ore is plentiful and food is scarce; measures whether agents trade for calories.",
  "season_ticks": 300,
  "env": {
    "seed": 42,
    "resources": {
      "ore": {
        "max": 4,
        "regen": 4
      },
      "food": {
        "max": 0.5,
        "regen": 0.5
      }
    },
    "anchors": [
      "honest-trader",
      "greedy-harvester"
    ]
  }
};

const check = await call<{ receipt: { warnings: unknown[] } }>('POST', '/scenarios/validate', scenario);
if (check.receipt.warnings.length) throw new Error(JSON.stringify(check.receipt.warnings));
const { scenario: saved } = await call<{ scenario: { id: string; hash: string } }>('POST', '/scenarios', scenario);

const runBody = { scenario_id: saved.id, roster: [{ "model": "<provider>/<model>", "name": "Kestrel" }, { "model": "<provider>/<model>", "name": "Heron" }], max_spend_usd: 2 };
const { run } = await call<{ run: { run_id: string } }>('POST', '/runs', runBody);

let r: { run: { status: string }; results: unknown };
do {
  await new Promise((f) => setTimeout(f, 30_000));
  r = await call('GET', `/runs/${run.run_id}`);
} while (!['finished', 'failed', 'cancelled'].includes(r.run.status));
console.log(r.run.status, r.results);

# Connect any MCP client to https://daishi.ai/mcp/studio with the token as a Bearer header
# (per-client configs on the MCP page), then hand the agent this:

You have the Daishi Studio tools. Read get_scenario_schema first. Design a
300-tick scenario where ore is abundant and food is scarce, with one
honest-trader and one greedy-harvester bot. Call validate_scenario until the
receipt has no warnings, then create_scenario. Then estimate_run for a roster
of two models of my choice and report the estimate. Do not call launch_run
until I say go.