Getting Started with Contexts
Let's build a loan approval Context that collects data from multiple sources and automatically runs your approval rule when everything's ready.
Create a Context
Go to Dashboard → Contexts and click Create Context.
Name it "Loan Application" and set application_id as the identity fact—this is what uniquely identifies each loan application flowing through the system.
Define Your Facts
In the Context Editor, add the facts your approval decision needs:
| Fact | Type | Required |
|---|---|---|
application_id | string | Yes |
credit_score | number | Yes |
annual_income | number | Yes |
employment_verified | boolean | Yes |
approval_decision | string | No (output) |
Mark facts as required if rules can't execute without them. Mark approval_decision as output only—your rule will write to it, not external systems.
Add a Derived Fact (Optional)
Derived facts calculate automatically from other facts. Add a debt-to-income ratio:
monthly_debt / (annual_income / 12)This updates whenever monthly_debt or annual_income changes.
Bind Your Rule
Open your loan approval rule, set its input schema to From Context, and select the Loan Application context. The rule will now read from context facts and write its decision back.
Test It
Use the Console tab to simulate data arriving:
Submit facts one at a time and watch the have/need arrays update. When you submit the last required fact, your rule executes automatically and writes approval_decision back to the context.
Using the API
Submit facts to a context instance via POST:
curl -X POST "https://api.rulebricks.com/api/v1/contexts/loan-application/APP-12345" \
-H "x-api-key: YOUR_API_KEY" \
-d '{ "credit_score": 720 }'The response shows current state:
{
"status": "pending",
"have": ["application_id", "credit_score"],
"need": ["annual_income", "employment_verified"]
}When the final required fact arrives, the response includes the rule execution:
{
"status": "complete",
"cascaded": [{
"rule": "loan-approval",
"result": { "approval_decision": "approved", "max_loan_amount": 250000 }
}]
}Next Steps
- Facts and Schema — Derived facts, history tracking, and schema design
- Progressive Execution — How auto-execution and cascades work
- Binding Rules — Connect rules to read from and write to contexts