القائمة
Use when the user asks about fraud detection, three-way matching anomalies, duplicate invoices, unusual payment patterns, or supplier concentration risk
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Dispatch ERP queries to Workers. Handles task creation, MinIO sync, state registration, and Matrix room dispatch.
Manager direct-to-MCP fast path for simple ERP data queries. Bypasses Workers entirely — calls honeybadge-nebula-mcp generate_query + validate_and_execute, then forwards results to user via contract 002.
Use when handling any natural language question about ERP data (suppliers, POs, invoices, payments, items, receipts, etc.)
Use when the user asks for analysis that requires decomposing a complex question into multiple queries (trend analysis, comparisons, aggregation across entities)
| name | anomaly-detection |
| description | Use when the user asks about fraud detection, three-way matching anomalies, duplicate invoices, unusual payment patterns, or supplier concentration risk |
Call the Python detection modules instead of raw mcporter CLI:
# Three-way matching (PO vs Receipt vs Invoice)
python3 -m anomaly_detection.lib.detect three-way --po-id "PO-2026-001"
# Duplicate invoice detection
python3 -m anomaly_detection.lib.detect duplicate-invoices --supplier-id "S001"
# Unusual payment patterns (last 90 days)
python3 -m anomaly_detection.lib.detect unusual-payments --days 90
# Supplier concentration risk
python3 -m anomaly_detection.lib.detect supplier-concentration --category "IT"
Pattern definitions and thresholds are in lib/patterns.py.
Implementation is in lib/detect.py.
lib/patterns.py -- do not hardcode in prompts