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Query Model and Templates

This page defines the core Auto query shape and copy/paste starters you can use before activation.

Query Shape​

{
  "conditions": { "AND": ["..."] },
  "actions": [
    {
      "stepId": "step_1",
      "type": "notify",
      "params": { "message": "..." }
    }
  ],
  "expiresIn": "24h"
}

Allowed action types:

  • webhook
  • notify
  • telegram
  • llm

Quick Action Snippets (for Builder Chat)​

Use these snippets inside your POST /v2/auto/chat prompt so the generated query includes delivery wiring.

Webhook​

Action requirements:
- action type: webhook
- deliver trigger payload to https://your-runner.example/auto/events
- keep payload concise and machine-readable

Telegram​

Action requirements:
- action type: telegram
- send alert to my bot/chat with symbol, trigger reason, and timestamp
- include severity label: info, warn, or high

LLM​

Action requirements:
- action type: llm
- return one decision: long, short, or no-trade
- include 3 bullet rationale points and confidence score
- I will fetch full output via sessions APIs

Copy/Paste Query Templates​

Use these as starting points with Validate Query before create.

Note:

  • action.params keys can vary by integration setup. Treat these as starter templates and adjust for your environment.

1) Breakout Alert (Webhook)​

{
  "conditions": {
    "AND": [
      {
        "source": "price",
        "method": "current",
        "args": { "symbol": "BTC" },
        "operator": ">",
        "value": 100000
      }
    ]
  },
  "actions": [
    {
      "stepId": "step_1",
      "type": "webhook",
      "params": { "url": "https://your-runner.example/auto/events" }
    }
  ],
  "expiresIn": "24h"
}

2) Downside Guardrail (Telegram)​

{
  "conditions": {
    "AND": [
      {
        "source": "price",
        "method": "current",
        "args": { "symbol": "ETH" },
        "operator": "<",
        "value": 2500
      }
    ]
  },
  "actions": [
    {
      "stepId": "step_1",
      "type": "telegram",
      "params": { "message": "ETH fell below 2500" }
    }
  ],
  "expiresIn": "24h"
}

3) Runner Handoff (Webhook + Notify)​

{
  "conditions": {
    "AND": [
      {
        "source": "price",
        "method": "current",
        "args": { "symbol": "SOL" },
        "operator": ">",
        "value": 220
      }
    ]
  },
  "actions": [
    {
      "stepId": "step_1",
      "type": "webhook",
      "params": { "url": "https://your-runner.example/auto/events" }
    },
    {
      "stepId": "step_2",
      "type": "notify",
      "params": { "message": "SOL trigger fired; runner notified" }
    }
  ],
  "expiresIn": "24h"
}

4) Triggered LLM Analysis​

{
  "conditions": {
    "AND": [
      {
        "source": "price",
        "method": "current",
        "args": { "symbol": "BTC" },
        "operator": ">",
        "value": 100000
      }
    ]
  },
  "actions": [
    {
      "stepId": "step_1",
      "type": "llm",
      "params": { "objective": "Analyze trigger context and return next action" }
    }
  ],
  "expiresIn": "24h"
}

5) Multi-Symbol Confirmation​

{
  "conditions": {
    "AND": [
      {
        "source": "price",
        "method": "current",
        "args": { "symbol": "BTC" },
        "operator": ">",
        "value": 100000
      },
      {
        "source": "price",
        "method": "current",
        "args": { "symbol": "ETH" },
        "operator": ">",
        "value": 3500
      }
    ]
  },
  "actions": [
    {
      "stepId": "step_1",
      "type": "notify",
      "params": { "message": "BTC and ETH confirmation trigger fired" }
    }
  ],
  "expiresIn": "24h"
}

Poll Response Shape​

GET /v2/auto/queries/{queryId} returns:

  • queryId
  • status
  • latestEvaluation
  • executions (from Athena executions data array)

Common Agent Flows​

Poll-Based LLM Flow​

1. POST /v2/auto/queries                               -> create query with action.type = "llm"
2. GET /v2/auto/queries/{queryId}                      -> poll until execution with sessionId appears
3. GET /v2/auto/queries/{queryId}/sessions/{sessionId} -> fetch full analysis

Webhook-Based LLM Flow​

1. POST /v2/auto/queries                               -> create with action.type = "llm" + callback webhook
2. Wait for webhook                                    -> receive session reference / output
3. Optional GET session fetch                          -> /v2/auto/queries/{queryId}/sessions/{sessionId}