oclaw/openclaw/qa/scenarios/media/image-understanding-attachment.md

# Image understanding from attachment

```yaml qa-scenario
id: image-understanding-attachment
title: Image understanding from attachment
surface: image-understanding
coverage:
  primary:
    - media.image-understanding
  secondary:
    - channels.qa-channel
objective: Verify an attached image reaches the agent model and the agent can describe what it sees.
successCriteria:
  - Agent receives at least one image attachment.
  - Final answer describes the visible image content in one short sentence.
  - The description mentions the expected red and blue regions.
docsRefs:
  - docs/help/testing.md
  - docs/tools/index.md
codeRefs:
  - src/gateway/server-methods/agent.ts
  - extensions/qa-lab/src/suite.ts
  - extensions/qa-lab/src/mock-openai-server.ts
execution:
  kind: flow
  summary: Verify an attached image reaches the agent model and the agent can describe what it sees.
  config:
    prompt: "Image understanding check: describe the top and bottom colors in the attached image in one short sentence."
    requiredColorGroups:
      - [red, scarlet, crimson]
      - [blue, azure, teal, cyan, aqua]
```

```yaml qa-flow
steps:
  - name: describes an attached image in one short sentence
    actions:
      - call: reset
      - set: outboundStartIndex
        value:
          expr: "state.getSnapshot().messages.filter((message) => message.direction === 'outbound').length"
      - call: runAgentPrompt
        args:
          - ref: env
          - sessionKey: agent:qa:image-understanding
            message:
              expr: config.prompt
            attachments:
              - mimeType: image/png
                fileName: red-top-blue-bottom.png
                content:
                  expr: imageUnderstandingValidPngBase64
            timeoutMs:
              expr: liveTurnTimeoutMs(env, 45000)
      - call: waitForOutboundMessage
        saveAs: outbound
        args:
          - ref: state
          - lambda:
              params: [candidate]
              expr: "candidate.conversation.id === 'qa-operator' && config.requiredColorGroups.every((group) => group.some((color) => normalizeLowercaseStringOrEmpty(candidate.text).includes(color)))"
          - expr: liveTurnTimeoutMs(env, 45000)
          - sinceIndex:
              ref: outboundStartIndex
      - set: missingColorGroup
        value:
          expr: "config.requiredColorGroups.find((group) => !group.some((candidate) => normalizeLowercaseStringOrEmpty(outbound.text).includes(candidate)))"
      - assert:
          expr: "!missingColorGroup"
          message:
            expr: "`missing expected colors in image description: ${outbound.text}`"
      # Image-processing assertion: verify the mock actually received an
      # image on the scenario-unique prompt. This is as strong as a
      # tool-call assertion for this scenario — unlike the
      # `source-docs-discovery-report` / `subagent-handoff` /
      # `config-restart-capability-flip` scenarios that rely on a real
      # tool call to satisfy the parity criterion, image understanding
      # is handled inside the provider's vision capability and does NOT
      # emit a tool call the mock can record as `plannedToolName`. The
      # `imageInputCount` field IS the tool-call evidence for vision
      # scenarios: it proves the attachment reached the provider, which
      # is the only thing an external harness can verify in mock mode.
      # Match on the scenario-unique prompt substring so the assertion
      # can't be accidentally satisfied by some other scenario's image
      # request that happens to share a debug log with this one.
      - set: imageRequest
        value:
          expr: "env.mock ? [...(await fetchJson(`${env.mock.baseUrl}/debug/requests`))].find((request) => String(request.prompt ?? '').includes('Image understanding check')) : null"
      - assert:
          expr: "!env.mock || (imageRequest && (imageRequest.imageInputCount ?? 0) >= 1)"
          message:
            expr: "`expected at least one input image on the Image understanding check request, got imageInputCount=${String(imageRequest?.imageInputCount ?? 0)}`"
    detailsExpr: outbound.text
```