{
  "sampling": {
    "rate": 0.25,
    "method": "random"
  }
}

{
  "media_buy_id": "mb_nike_reddit_q1",
  "artifacts": [
    {
      "record_id": "imp_12345",
      "timestamp": "2025-01-15T10:30:00Z",
      "package_id": "pkg_feed_standard",
      "artifact": {
        "property_id": {"type": "domain", "value": "reddit.com"},
        "artifact_id": "r_fitness_abc123",
        "assets": [
          {"type": "text", "role": "title", "content": "Best protein sources for muscle building", "language": "en"},
          {"type": "text", "role": "paragraph", "content": "Looking for recommendations on high-quality protein sources...", "language": "en"},
          {"type": "image", "url": "https://cdn.reddit.com/fitness-image.jpg", "alt_text": "Person lifting weights"}
        ]
      },
      "country": "US",
      "channel": "social",
      "brand_context": {"brand_id": "nike_global", "sku_id": "air_max_2025"},
      "local_verdict": "pass"
    },
    {
      "record_id": "imp_12346",
      "timestamp": "2025-01-15T10:35:00Z",
      "package_id": "pkg_feed_standard",
      "artifact": {
        "property_id": {"type": "domain", "value": "reddit.com"},
        "artifact_id": "r_news_politics_456",
        "assets": [
          {"type": "text", "role": "title", "content": "Election Results Analysis", "language": "en"},
          {"type": "text", "role": "paragraph", "content": "The latest polling data shows...", "language": "en"}
        ]
      },
      "country": "US",
      "channel": "social",
      "brand_context": {"brand_id": "nike_global", "sku_id": "air_max_2025"},
      "local_verdict": "fail"
    }
  ],
  "sampling_info": {
    "total_deliveries": 100000,
    "sampled_count": 1000,
    "effective_rate": 0.01,
    "method": "random"
  },
  "pagination": {
    "cursor": "eyJvZmZzZXQiOjEwMDB9",
    "has_more": true
  }
}

# Get artifacts from seller
artifacts_response = seller_agent.get_media_buy_artifacts(
    media_buy_id="mb_nike_reddit_q1",
    sampling={"rate": 0.25, "method": "random"}
)

# Convert to validation records
records = [
    {
        "record_id": a["record_id"],
        "timestamp": a["timestamp"],
        "media_buy_id": artifacts_response["media_buy_id"],
        "artifact": a["artifact"],
        "country": a.get("country"),
        "channel": a.get("channel"),
        "brand_context": a.get("brand_context")
    }
    for a in artifacts_response["artifacts"]
]

# Validate against verification agent
validation = verification_agent.validate_content_delivery(
    standards_id="nike_brand_safety",
    records=records
)

# Check for drift between local and verified verdicts
for i, result in enumerate(validation["results"]):
    local = artifacts_response["artifacts"][i]["local_verdict"]
    verified = result["verdict"]
    if local != verified:
        print(f"Drift detected: {result['record_id']} - local={local}, verified={verified}")

# Get only artifacts that failed local evaluation
failures = seller_agent.get_media_buy_artifacts(
    media_buy_id="mb_nike_reddit_q1",
    sampling={"method": "failures_only"},
    limit=100
)

# Verify these were correctly flagged
validation = verification_agent.validate_content_delivery(
    standards_id="nike_brand_safety",
    records=[{"record_id": a["record_id"], "artifact": a["artifact"]}
             for a in failures["artifacts"]]
)

# Check false positive rate
false_positives = sum(1 for r in validation["results"] if r["verdict"] == "pass")
print(f"False positive rate: {false_positives / len(failures['artifacts']):.1%}")