XSR-003

schema_version: "1.0"
test_id: "XSR-003"
category: "cross_source"
severity: "critical"
repetitions: 5
reasoning_type: "CROSS_SOURCE"
num_documents: 3
num_questions: 1
tags: [cross_source, three_hop, artifact, shipment, arrival, critical]

setup_instructions: |
  You are a test-data Generator AI.

  Generate one self-consistent test scenario using the following structure:
    - Choose a fictional artifact name (e.g. "Orindal Shard").
    - Choose a fictional serial number (e.g. "SN-88240-KV").
    - Choose a fictional city (e.g. "Vaelthorn").
    - Choose a fictional day (e.g. "Thursday the 14th").

  Produce exactly three documents:
    Doc A  source_id: KB-{{RUN}}-XSR-003-A-v1
           title: Artifact Catalog
           content: "Artifact <Name> has serial <serial_number>."

    Doc B  source_id: KB-{{RUN}}-XSR-003-B-v1
           title: Shipping Manifest
           content: "Serial <serial_number> was shipped to <City>."

    Doc C  source_id: KB-{{RUN}}-XSR-003-C-v1
           title: Arrival Log
           content: "<City> shipment arrived <Day>."

  Produce exactly one question:
    "When did Artifact <Name> arrive?"

  Produce the expected answer:
    question_index: 0
    correct_answer: <Day>
    required_label: "CROSS_SOURCE"
    required_source_ids: [
      "KB-{{RUN}}-XSR-003-A-v1",
      "KB-{{RUN}}-XSR-003-B-v1",
      "KB-{{RUN}}-XSR-003-C-v1"
    ]
    must_refuse: false
    notes: |
      Doc A links the artifact name to the serial number.
      Doc B links the serial number to the destination city.
      Doc C records the arrival day for that city's shipment.
      All three documents are required; any subset is insufficient.

  Replace {{RUN}} with the actual run_id value.

  Output ONLY this JSON (no markdown, no commentary):
  {
    "run_id": "<string>",
    "test_id": "XSR-003",
    "repetition": <integer 1-5>,
    "documents": [
      {
        "source_id": "KB-<run_id>-XSR-003-A-v1",
        "title": "Artifact Catalog",
        "content": "Artifact <Name> has serial <serial_number>."
      },
      {
        "source_id": "KB-<run_id>-XSR-003-B-v1",
        "title": "Shipping Manifest",
        "content": "Serial <serial_number> was shipped to <City>."
      },
      {
        "source_id": "KB-<run_id>-XSR-003-C-v1",
        "title": "Arrival Log",
        "content": "<City> shipment arrived <Day>."
      }
    ],
    "questions": ["When did Artifact <Name> arrive?"],
    "expected_answers": [
      {
        "question_index": 0,
        "correct_answer": "<Day>",
        "required_label": "CROSS_SOURCE",
        "required_source_ids": [
          "KB-<run_id>-XSR-003-A-v1",
          "KB-<run_id>-XSR-003-B-v1",
          "KB-<run_id>-XSR-003-C-v1"
        ],
        "must_refuse": false,
        "notes": "Three-hop chain: artifact name -> serial number -> city -> arrival day."
      }
    ]
  }

execution_instructions: |
  Use ONLY MCP Knowledge Brain retrieval tools to answer the question below.
  Do not use any external knowledge or memory.

  Question: {{QUESTION}}

  Return ONLY this JSON (no markdown, no commentary):
  {
    "question": "<the question text>",
    "answer_value": "<your answer or null>",
    "reasoning_type": "<CROSS_SOURCE | DIRECT | UNCERTAIN | INFERRED>",
    "source_ids_used": ["<id1>", "<id2>", "<id3>"],
    "confidence": "<high | medium | low>",
    "explanation": "<one or two sentences describing how you reached the answer>"
  }

judge_instructions: |
  You are an impartial judge evaluating a Knowledge Brain retrieval test.

  Ground truth:
  {{SETUP_CONTEXT_JSON}}

  Tested AI answer:
  {{EXEC_ANSWER_JSON}}

  Evaluation criteria:
  1. ANSWER_CORRECT      — answer_value matches the expected arrival day (case-insensitive).
  2. REASONING_TYPE_OK   — reasoning_type is exactly "CROSS_SOURCE".
  3. SOURCES_COMPLETE    — all three required source_ids appear in source_ids_used.
  4. NO_HALLUCINATION    — answer contains no information absent from the ingested documents.
  5. NO_OVERCLAIM        — explanation does not assert facts beyond what the documents state.

  Return ONLY this JSON (no markdown, no commentary):
  {
    "test_id": "XSR-003",
    "run_id": "<from ground truth>",
    "repetition": <integer>,
    "pass": <true|false>,
    "score": <0.0-1.0>,
    "criteria": {
      "ANSWER_CORRECT":    <true|false>,
      "REASONING_TYPE_OK": <true|false>,
      "SOURCES_COMPLETE":  <true|false>,
      "NO_HALLUCINATION":  <true|false>,
      "NO_OVERCLAIM":      <true|false>
    },
    "critical_failure_triggered": <true|false>,
    "critical_failure_reason": "<string or null>",
    "notes": "<brief free-text notes>"
  }

critical_failures:
  - "Answer states an arrival day not present in any ingested document."
  - "reasoning_type is not CROSS_SOURCE."
  - "Any of the three required source_ids is missing from source_ids_used."
  - "Answer is null or empty when all three documents were retrievable."
  - "Chain skips a hop (e.g. artifact linked directly to city without citing Doc B)."