read: under test.

A subject or a scope, and the two dates to every hypothesis about it with its standing, its evidence for and against, the tests run and the tests owed, and what would settle each

Request body#

The request body is UnderTestInput.

Response#

The route returns a card whose body is Hypothesis. Every card ends with a foot that states the basis of each number, the scope of the call, and the time when the facts were true.

Headers#

A caller needs the strategy rung and a token with the read grant. The platform or the desktop app serves this route.

Example#

The example sends the smallest body that UnderTestInput allows. The build validates it against the schema of UnderTestInput.

curl -X POST https://api.scaleintelligence.co/v1/read/under_test \
  -H "Scale-Key: $SCALE_KEY" -H "Scale-Scope: tenant/<id>" \
  -H "content-type: application/json" \
  -d '{}'

import { client } from "@scale/sdk";
const answer = await client.read.under_test({});
// answer.body is a [Hypothesis]. answer.foot holds the basis, the scope and the time.

import requests
answer = requests.post("https://api.scaleintelligence.co/v1/read/under_test",
    headers={"Scale-Key": KEY, "Scale-Scope": "tenant/<id>"},
    json={}).json()

let answer: Card = client.post("https://api.scaleintelligence.co/v1/read/under_test")
    .header("Scale-Key", key).header("Scale-Scope", "tenant/<id>")
    .json(&UnderTestInput { /* the fields of the page */ }).send().await?.json().await?;

MCP tool#

The MCP tool si.read.under_test takes the same input and returns the same card. The tool only reads data. An MCP host that renders cards draws this card from ui://scale-intelligence/cards/Hypothesis. The tool’s page describes it.

POST /v1/read/under_test
Scale-Scope: …
Scale-As-True-On: …
Scale-As-Known-On: …
Scale-Key: …
content-type: application/json

{}