Manage Context via Context Object

The Context Object is the central runtime state container for every workflow execution—capturing inputs, node states, outputs, and metadata across the full lifecycle of a run.

Overview

Every workflow execution has a single Context Object that updates dynamically as the workflow progresses. It serves as the shared memory layer that nodes read from and write to, enabling data to flow through the entire pipeline. What it tracks:

Run Metadata - Identifiers, timestamps, and workflow configuration (startDate, status, flowType, appId, versionId, cfProcessId)
Execution State - Each node’s progress and outcome (steps, branch, activeSteps)
Environment & Config - Runtime parameters and settings (env, agentTimeout, asyncExecDetails)

Structure

Top-Level Fields

Category	Key Fields	Description
Run Metadata	`startDate`, `status`, `flowType`, `appId`, `versionId`, `cfProcessId`	Identifiers and timestamps for the workflow instance
Execution State	`steps`, `branch`, `activeSteps`, `status`	Each node’s progress and outcome
Environment & Config	`env`, `agentTimeout`, `asyncExecDetails`	Runtime and environment parameters

The `steps` Object

steps is the most critical part of the Context Object—a map indexed by node name or ID that holds the state of each node in the workflow.

"steps": {
  "NodeNameA": { ... },
  "NodeNameB": { ... },
  "NodeNameC": { ... }
}

Each node entry contains:

Field	Description
`input`	Data received by the node at execution time, from previous nodes or user input
`output`	Result produced by the node—model outputs, processed data, or API responses
`statusCode` / `isSuccessful`	Whether execution succeeded, failed, or was skipped
`logs`	Log text or debug messages generated by the node
`executionTime`, `totalTime`, `pausedAt`, `resumedAt`	Node-level timing data
`reqObj` / `resObj`	For model-invoking nodes: raw request and response envelopes
`metadata`	Node-specific information such as schema references, task IDs, or external job handles

Example node structure:

"steps": {
  "ExampleNode": {
    "input": {
      "parameters": { "param1": "value1" },
      "contextRefs": { "previousNodeOutput": "..." }
    },
    "output": {
      "result": "some value",
      "summary": "optional explanation",
      "structuredData": { "key": "value" }
    },
    "statusCode": 200,
    "isSuccessful": true,
    "logs": "Node executed successfully",
    "executionTime": "1250ms",
    "reqObj": {
      "endpoint": "https://api.example.com/run",
      "body": { "input": "..." }
    },
    "resObj": {
      "status": 200,
      "data": { "response": "..." }
    },
    "metadata": {
      "model": "gpt-5",
      "nodeType": "LLM",
      "dependencies": ["SchemaRetriever", "Sanitizer"]
    }
  }
}

Lifecycle

The steps map is populated sequentially as the workflow executes:

Initialization - The steps object starts empty.
Node Execution - An entry is created for each node as it begins running.
Completion - Outputs and timing data are appended.
Error Handling - Logs and status are updated; branch reflects any failures.

Node Types Reference

Node Type	Typical Fields	Description
Input / Start Node	`user_query`, `metadata`	Captures the initial user request or input values
API Node	`body`, `statusCode`, `totalTime`	Fetches external data from APIs, schemas, or databases
AI Node	`reqObj`, `resObj`, `modelElapsedTime`, `inferenceTime`	Records prompt and response data for auditability

Loop Node Context

When a loop node executes, it creates its own context object tracking the loop’s progress and results.

Structure

{
  "loopId": "string",
  "startTime": "timestamp",
  "iterationCount": "number",
  "inputs": ["array of input values"],
  "outputArray": ["array of iteration results"],
  "totalCount": "number",
  "childNodesExecuted": "number"
}

Field	Type	Description
`loopId`	String	Unique identifier for the loop node, matching the node ID in the flow
`startTime`	Timestamp	When the loop started executing
`iterationCount`	Number	Number of iterations completed
`inputs`	Array	The original list of items the loop is processing
`outputArray`	Array of Objects	Results from each iteration, in execution order
`totalCount`	Number	Total number of items processed—equal to `inputs.length`
`childNodesExecuted`	Number	Total child nodes that ran across all iterations

The `outputArray`

Each item in outputArray represents one iteration’s result:

Maintains the same order as the inputs array.
Each result is wrapped in an output object.
The structure of each output depends on what the loop produces.

Example

Inputs: ["user1@example.com", "user2@example.com"]

{
  "loopId": "Add2DB_0",
  "startTime": "2025-11-12T09:23:05.306Z",
  "iterationCount": 2,
  "inputs": ["user1@example.com", "user2@example.com"],
  "outputArray": [
    {
      "output": {
        "success": "user1@example.com added to the Employee Database",
        "processId": "cfp-d687dc0a-4608-4f41-a4f3-68a691d9dce6"
      }
    },
    {
      "output": {
        "success": "user2@example.com added to the Employee Database",
        "processId": "cfp-5fb1718e-5962-4f43-b1af-b52bda936b09"
      }
    }
  ],
  "totalCount": 2,
  "childNodesExecuted": 10
}

Accessing Loop Data

Inside the loop – Use special context variables scoped to the current iteration:

Variable	Description	Example
`{{context.currentItem}}`	The item currently being processed	`user1@example.com` in the first iteration
`{{context.currentIndex}}`	Zero-based index of the current item	`0` for the first iteration
`{{context.currentOutput[x]}}`	Output from a previous iteration	`{{context.currentOutput[0]}}` returns the first iteration’s output

Outside the loop - Access full results using the loop node’s ID:

Variable	Description
`{{context.steps.Loop0001.output}}`	Complete array of all iteration results
`{{context.steps.Loop0001.output[x]}}`	A specific iteration’s result

Using the Context Object

Cross-Node Referencing

Nodes reference each other’s data through context interpolation using the {{ }} syntax. Values are resolved at runtime—no code required.

"steps": {
  "SchemaRetriever": {
    "output": { "schema": [ ... ] }
  },
  "QueryGenerator": {
    "input": {
      "schema": "{{steps.SchemaRetriever.output.schema}}"
    }
  }
}

Reference Patterns

{{context.appId}}
{{context.steps.QueryGenerator.output.sql_query}}
{{context.schema[0].column_name}}

context refers to the full Context Object.
steps provides scoped access to node-level data.
References work anywhere: input fields, API parameters, LLM prompts, and conditions.

Evaluation Behavior

Lazy resolution - Values are resolved immediately before each node executes.
Missing keys - Resolve to null (or an empty string in string contexts).
Circular references - Automatically detected and blocked.

Typing {{ in any field that supports context variables displays a dropdown of all available variables, grouped by node—including environment variables defined at the workflow level.

Extending with Script Nodes

Script Nodes let you extend the Context Object programmatically during execution. This is useful for storing computed values, passing control variables across nodes, and persisting contextual data for downstream use.

JavaScript

// Add a simple key-value pair
context.newKey = "Hello World";

// Store structured data
context.customData = {
  runId: context.cfProcessId,
  stage: "validation",
  timestamp: new Date().toISOString()
};

// Access it in later nodes
console.log(context.customData.stage);

Python

# Add or modify keys in the context dictionary
context['newKey'] = "Hello World"

# Store complex objects
context['customData'] = {
    "runId": context.get('cfProcessId'),
    "stage": "validation",
    "timestamp": datetime.now().isoformat()
}

# Retrieve later
print(context['customData']['stage'])

Guidelines

Use camelCase naming (customerInfo, retryCounter, tempResults)
Do not override reserved keys: steps, branch, status, dbquery
Keep data lightweight—avoid storing large arrays or raw API responses
All keys added to the context are accessible downstream via {{context.<key>}}

Best Practices

Use consistent node naming for traceability (e.g., QueryGenerator, DataCleaner).
Mask sensitive data before writing it to the context.
Prefer declarative references ({{ ... }}) for readability whenever possible.
Use Script Nodes only when dynamic or computed context manipulation is required.

Building Agents

Platform Services

Administration

References

Manage Context via Context Object

Overview

Structure

Top-Level Fields

The `steps` Object

Lifecycle

Node Types Reference

Loop Node Context

Structure

The `outputArray`

Example

Accessing Loop Data

Using the Context Object

Cross-Node Referencing

Reference Patterns

Evaluation Behavior

Extending with Script Nodes

JavaScript

Python

Guidelines

Best Practices

Building Agents

Platform Services

Administration

References

​Overview

​Structure

​Top-Level Fields

​The steps Object

​Lifecycle

​Node Types Reference

​Loop Node Context

​Structure

​The outputArray

​Example

​Accessing Loop Data

​Using the Context Object

​Cross-Node Referencing

​Reference Patterns

​Evaluation Behavior

​Extending with Script Nodes

​JavaScript

​Python

​Guidelines

​Best Practices

Overview

Structure

Top-Level Fields

The `steps` Object

Lifecycle

Node Types Reference

Loop Node Context

Structure

The `outputArray`

Example

Accessing Loop Data

Using the Context Object

Cross-Node Referencing

Reference Patterns

Evaluation Behavior

Extending with Script Nodes

JavaScript

Python

Guidelines

Best Practices