Amazon DeepRacer · Agentic Access

Amazon DeepRacer Agentic Access

x-agentic-access generated

Amazon DeepRacer exposes 10 API operations that an AI agent could call, of which 2 are state-changing ‘acting’ operations. This is a recommended x-agentic-access execution contract — the scope, audience, consequence tier, short-lived token constraints, and escalation each action should carry before it is handed to an autonomous agent.

By consequence: 8 read and 2 write.

Contracts are classified heuristically from the provider’s OpenAPI and refresh on every APIs.io network build; audience is bound per deployment. The model follows Curity’s Access Intelligence (apidays Munich 2026). Browse every provider’s agent contracts at agentic-access.apis.io.

Autonomous VehiclesMachine LearningReinforcement LearningRobotics

Operations: 10 Acting: 2 Human-in-the-loop: 0 Method: generated

By consequence

read 8 write 2

Source

Agentic Access

generated: '2026-07-15'
method: generated
source: openapi/amazon-deepracer-openapi.yml
description: Recommended x-agentic-access execution contracts, classified heuristically from
  the OpenAPI. A governance starting point for exposing this API to AI agents — review and bind
  audience per deployment. See research/curity/agentic-governance/.
summary:
  operations: 10
  by_action_class:
    connected: 8
    acting: 2
  by_consequence:
    read: 8
    write: 2
  human_in_the_loop_required: 0
operations:
- path: /20201101/cars
  method: get
  operationId: listCars
  x-agentic-access:
    action-class: connected
    consequence: read
    subject: optional
    token:
      max-ttl: 3600
    audit: none
- path: /20201101/cars/{arn}
  method: get
  operationId: getCar
  x-agentic-access:
    action-class: connected
    consequence: read
    subject: optional
    token:
      max-ttl: 3600
    audit: none
- path: /20201101/cars/{arn}
  method: patch
  operationId: updateCar
  x-agentic-access:
    action-class: acting
    consequence: write
    subject: required
    audience: null
    token:
      max-ttl: 900
    escalation:
      human-in-the-loop: conditional
      triggers:
      - abnormal
      - high-value
    audit: required
- path: /20201101/models
  method: get
  operationId: listModels
  x-agentic-access:
    action-class: connected
    consequence: read
    subject: optional
    token:
      max-ttl: 3600
    audit: none
- path: /20201101/models/{modelArn}
  method: get
  operationId: getModel
  x-agentic-access:
    action-class: connected
    consequence: read
    subject: optional
    token:
      max-ttl: 3600
    audit: none
- path: /20201101/models/{modelArn}
  method: delete
  operationId: deleteModel
  x-agentic-access:
    action-class: acting
    consequence: write
    subject: required
    audience: null
    token:
      max-ttl: 900
    escalation:
      human-in-the-loop: conditional
      triggers:
      - abnormal
      - high-value
    audit: required
- path: /20201101/leaderboards
  method: get
  operationId: listLeaderboards
  x-agentic-access:
    action-class: connected
    consequence: read
    subject: optional
    token:
      max-ttl: 3600
    audit: none
- path: /20201101/leaderboards/{arn}
  method: get
  operationId: getLeaderboard
  x-agentic-access:
    action-class: connected
    consequence: read
    subject: optional
    token:
      max-ttl: 3600
    audit: none
- path: /20201101/leaderboards/{arn}/rankings
  method: get
  operationId: listLeaderboardSubmissions
  x-agentic-access:
    action-class: connected
    consequence: read
    subject: optional
    token:
      max-ttl: 3600
    audit: none
- path: /20201101/tracks
  method: get
  operationId: listTracks
  x-agentic-access:
    action-class: connected
    consequence: read
    subject: optional
    token:
      max-ttl: 3600
    audit: none