NODEDC_1C/docs/HARD_SEMANTIC/anomaly_engine_spec.md

Anomaly Engine Spec (Layer 5 MVP)

Date: 2026-03-23
Status: implemented in canonical_layer/features.py

1. Engine role

Detect suspicious patterns from canonical data and refresh operations without direct write access to 1C.

2. Input data

• canonical_entities
• canonical_links
• refresh_runs (for freshness context)
• previous successful feature_runs and feature_metrics (for drift context)

3. Implemented anomaly rules

3.1 no_canonical_data

Trigger:

• canonical entity count is zero.

Severity:

• high

3.2 empty_display_share_high

Trigger:

• per-source-entity count >= 50
• and empty_display_share >= 0.2

Severity:

• medium

3.3 high_link_degree

Trigger:

• entity link count exceeds dynamic threshold max(10, mean + 3*std)

Severity:

• medium or high by score multiplier over threshold.

3.4 missing_refresh_baseline

Trigger:

• no successful refresh run exists.

Severity:

• high

3.5 stale_refresh

Trigger:

• refresh_age_hours exceeds configured threshold (ANOMALY_STALE_REFRESH_THRESHOLD_HOURS)

Severity:

• high

3.6 entity_count_drift

Trigger:

• previous successful feature run exists
• absolute drift ratio for entity_count is >= 0.3
• and absolute count difference >= 10

Severity:

• medium or high (if drift ratio >= 1.0)

4. Output contract

Each anomaly signal contains:

• signal_type
• severity
• scope
• scope_id
• score
• details
• is_active

5. Execution

• API: POST /features/run
• CLI: python scripts/run_features.py
• PowerShell: scripts/run_features.ps1