Context recall
Checks if your retrieved context contains the information needed to generate a known correct answer.
Use when: You have ground truth answers and want to verify your retrieval finds supporting evidence.
How it works: Breaks the expected answer into statements and checks if each can be attributed to the context. Score = attributable statements / total statements.
Example:
Expected: "Python was created by Guido van Rossum in 1991"
Context: "Python was released in 1991"
Score: 0.5 (year ✓, creator ✗)
Configuration
assert:
  - type: context-recall
    value: 'Python was created by Guido van Rossum in 1991'
    threshold: 1.0 # Context must support entire answer
Required fields
value- Expected answer/ground truthcontext- Retrieved text (in vars or viacontextTransform)threshold- Minimum score 0-1 (default: 0)
Full example
tests:
  - vars:
      query: 'Who created Python?'
      context: 'Guido van Rossum created Python in 1991.'
    assert:
      - type: context-recall
        value: 'Python was created by Guido van Rossum in 1991'
        threshold: 1.0
Dynamic context extraction
For RAG systems that return context with their response:
# Provider returns { answer: "...", context: "..." }
assert:
  - type: context-recall
    value: 'Expected answer here'
    contextTransform: 'output.context' # Extract context field
    threshold: 0.8
Limitations
- Binary attribution (no partial credit)
 - Works best with factual statements
 - Requires known correct answers
 
Related metrics
context-relevance- Is retrieved context relevant?context-faithfulness- Does output stay faithful to context?