docs: apply fleet-template (16-artifact scaffold)

Adds missing standard artifacts:
- README.md (if missing)
- AGENTS.md (AI agent contract)
- PLAN.md (current sprint)
- STATUS.md (where we are)
- DEVELOPMENT.md (dev workflow)
- DEPLOYMENT.md (deploy procedure)
- TESTING.md (test strategy)
- DECISIONS.md (ADR index + templates)
- .github/CODEOWNERS
- .github/workflows/ci.yml

Preserves all existing artifacts.

Refs: RugMunchMedia/fleet-template

tests/test_quality.py

@@ -0,0 +1,76 @@
+"""Tests for data quality SLA dashboard."""
+
+from quality import (
+    compute_completeness,
+    compute_freshness,
+    compute_null_rate,
+    detect_anomalies,
+)
+
+
+def test_compute_completeness_full() -> None:
+    data = {"name": "Alice", "age": 30, "email": "alice@example.com"}
+    result = compute_completeness(data)
+    assert result["score"] == 100.0
+    assert result["filled_fields"] == 3
+
+
+def test_compute_completeness_partial() -> None:
+    data = {"name": "Alice", "age": None, "email": ""}
+    result = compute_completeness(data)
+    assert result["score"] < 100
+
+
+def test_compute_completeness_empty() -> None:
+    result = compute_completeness({})
+    assert result["score"] == 0
+
+
+def test_compute_completeness_list() -> None:
+    data = [{"a": 1, "b": 2}, {"a": 3, "b": None}, {"a": 5, "b": 6}]
+    result = compute_completeness(data)
+    assert result["record_count"] == 3
+    assert result["score"] > 0
+
+
+def test_compute_freshness_fresh() -> None:
+    import time
+
+    data = {"timestamp": time.time()}
+    result = compute_freshness(data, max_age_seconds=3600)
+    assert result["fresh"] is True
+
+
+def test_compute_freshness_stale() -> None:
+    data = {"timestamp": 1000000}  # Old timestamp
+    result = compute_freshness(data, max_age_seconds=3600)
+    assert result["fresh"] is False
+
+
+def test_compute_null_rate() -> None:
+    data = {"a": 1, "b": None, "c": "", "d": 4}
+    result = compute_null_rate(data)
+    assert result["b"]["null_rate"] == 100.0
+    assert result["c"]["empty_rate"] == 100.0
+    assert result["a"]["null_rate"] == 0.0
+
+
+def test_detect_anomalies_empty_result() -> None:
+    anomalies = detect_anomalies({}, {"key": "value"})
+    assert len(anomalies) == 1
+    assert anomalies[0]["type"] == "empty_result"
+
+
+def test_detect_anomalies_missing_field() -> None:
+    anomalies = detect_anomalies({"a": 1}, {"a": 1, "b": 2})
+    assert any(a["type"] == "missing_field" for a in anomalies)
+
+
+def test_detect_anomalies_value_swing() -> None:
+    anomalies = detect_anomalies({"price": 200}, {"price": 10})
+    assert any(a["type"] == "value_swing" for a in anomalies)
+
+
+def test_detect_anomalies_no_previous() -> None:
+    anomalies = detect_anomalies({"a": 1}, None)
+    assert len(anomalies) == 0