read: propensity.

A lead, a move or a play, and which faces, actors or content or both (`PropensityInput`) to every eligible actor and every fitting content with the chance, its interval, its basis and the policy's odds, and the one the policy would choose (`PropensityAnswer`)

Request body#

The request body is PropensityInput.

Response#

The route returns a card whose body is PropensityAnswer. 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 serves this route.

Example#

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

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

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

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

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

MCP tool#

The MCP tool si.read.propensity 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/PropensityAnswer. The tool’s page describes it.

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

{
  "lead": "…",
  "faces": []
}