openclaw/qa/scenarios/memory/memory-recall.yaml

title: Memory recall after context switch

# This scenario deliberately stays prose-only and does NOT gate on a
# `/debug/requests` tool-call assertion, even though it is one of the
# scenarios in the parity pack. The adversarial review in the umbrella
# #64227 thread called this out as a coverage gap, but the underlying
# behavior the scenario tests is legitimately prose-shaped: the agent is
# supposed to pull a prior-turn fact ("ALPHA-7") back across an
# intervening context switch and reply with the code. In a real
# conversation, the model can do this EITHER by calling a memory-search
# tool (which the qa-lab mock server doesn't currently expose) OR by
# reading the fact directly from prior-turn context in its own
# conversation window. Both strategies are valid parity behavior.
#
# Forcing a `plannedToolName` assertion here would either require
# extending the mock with a synthetic `memory_search` tool lane (PR O
# scope, not PR J) or fabricating a tool-call requirement the real
# providers never implement. Either path would make this scenario test
# the harness, not the models. So we keep it prose-only, covered by the
# `recallExpectedAny` / `rememberAckAny` assertions above, and flag the
# exception explicitly rather than silently.
#
# Criterion 2 of the parity completion gate (no fake progress or fake
# tool completion) is enforced for this scenario through the parity
# report's failure-tone fake-success detector: a scenario marked `pass`
# whose details text matches patterns like "timed out", "failed to",
# "could not" gets flagged via `SUSPICIOUS_PASS_FAILURE_TONE_PATTERNS`
# in `extensions/qa-lab/src/agentic-parity-report.ts`. Positive-tone
# detection was removed because it false-positives on legitimate passes
# where the details field is the model's outbound prose.

scenario:
  id: memory-recall
  surface: memory
  coverage:
    primary:
      - memory.recall
  objective: Verify the agent can store a fact, switch topics, then recall the fact accurately later.
  successCriteria:
    - Agent acknowledges the seeded fact.
    - Agent later recalls the same fact correctly.
    - Recall stays scoped to the active QA conversation.
  docsRefs:
    - docs/help/testing.md
  codeRefs:
    - extensions/qa-lab/src/scenario.ts
  execution:
    kind: flow
    summary: Verify the agent can store a fact, switch topics, then recall the fact accurately later.
    config:
      requiredChannelDriver: qa-channel
      resetDurableMemory: true
      rememberPrompt: "Please remember this fact for later: the QA canary code is ALPHA-7. Use your normal memory mechanism, avoid manual repo cleanup, and reply exactly `Remembered ALPHA-7.` once stored."
      rememberAckAny:
        - remembered alpha-7
      recallPrompt: "What was the QA canary code I asked you to remember earlier? Reply with the code only, plus at most one short sentence."
      recallExpectedAny:
        - alpha-7

flow:
  steps:
    - name: stores the canary fact
      actions:
        - assert:
            expr: "!config.resetDurableMemory || true"
        - call: fs.rm
          args:
            - expr: "path.join(env.gateway.workspaceDir, 'MEMORY.md')"
            - force: true
        - call: fs.rm
          args:
            - expr: "path.join(env.gateway.workspaceDir, 'memory', `${formatMemoryDreamingDay(Date.now())}.md`)"
            - force: true
        - call: reset
        - call: runAgentPrompt
          args:
            - ref: env
            - sessionKey: agent:qa:memory
              message:
                expr: config.rememberPrompt
              timeoutMs:
                expr: liveTurnTimeoutMs(env, 60000)
        - set: rememberAckAny
          value:
            expr: config.rememberAckAny.map(normalizeLowercaseStringOrEmpty)
        - call: waitForOutboundMessage
          saveAs: outbound
          args:
            - ref: state
            - lambda:
                params: [candidate]
                expr: "candidate.conversation.id === 'qa-operator' && rememberAckAny.some((needle) => normalizeLowercaseStringOrEmpty(candidate.text).includes(needle))"
      detailsExpr: outbound.text
    - name: recalls the same fact later
      actions:
        - call: runAgentPrompt
          args:
            - ref: env
            - sessionKey: agent:qa:memory
              message:
                expr: config.recallPrompt
              timeoutMs:
                expr: liveTurnTimeoutMs(env, 60000)
        - set: recallExpectedAny
          value:
            expr: config.recallExpectedAny.map(normalizeLowercaseStringOrEmpty)
        - call: waitForCondition
          saveAs: outbound
          args:
            - lambda:
                expr: "state.getSnapshot().messages.filter((candidate) => candidate.direction === 'outbound' && candidate.conversation.id === 'qa-operator' && recallExpectedAny.some((needle) => normalizeLowercaseStringOrEmpty(candidate.text).includes(needle))).at(-1)"
            - 20000
      detailsExpr: outbound.text