agent-e2e-validation

name	agent-e2e-validation
description	End-to-end manual validation of all 26 retail agents: infrastructure recovery, HTTP/EventHub/MCP connectivity, and graded prompt testing from none to high complexity — simulating real user behavior against deployed public endpoints.
argument-hint	Run the full agent validation suite, or specify a domain: ecommerce, crm, inventory, logistics, product-management, truth-layer.
user-invocable	true
disable-model-invocation	false

Agent E2E Validation: Full-Stack Behavioral Testing

Purpose

Simulate real user and operator behavior against every deployed agent service to validate that the full agentic retail platform works end-to-end. This is not automated unit/integration testing — it is a structured manual exploration where each agent is treated as an independent solution, exercised through its public HTTP endpoints, asynchronous Event Hub triggers, and MCP tool surface.

When To Use

Use this skill when you need to:

• Validate all 26 agents are reachable and responding correctly after deployment.
• Run behavioral prompts of varying complexity against each agent domain.
• Verify Event Hub async processing chains are firing and completing.
• Test MCP tool calls between agents through APIM routing.
• Perform pre-demo or post-deployment confidence checks on the full platform.
• Diagnose issues across the distributed agent mesh.

Trigger phrases: "run e2e validation", "test all agents", "validate deployment", "agent smoke test", "behavioral test suite", "validate agent endpoints".

MANDATORY: Pre-Flight Infrastructure Recovery

ALWAYS start here. Do not skip this section. Every validation session begins with infrastructure recovery.

The dev environment is subject to MCAPSGov nightly automation that stops PostgreSQL, disables Entra AD auth, and shuts down the AKS cluster. The CRUD service (and by extension every agent that depends on it) will be completely down until recovery completes.

Step 0: Run the Start-Dev-Environment Script

./scripts/start-dev-environment.ps1

What it does (in order):

1. Starts PostgreSQL Flexible Server (AKS pods depend on it being ready first)
2. Polls until PostgreSQL reports Ready state (up to 30 attempts, 10s each)
3. Re-enables Entra AD authentication if MCAPSGov disabled it
4. Re-registers the CRUD service managed identity as PostgreSQL Entra admin if dropped
5. Starts the AKS cluster if stopped
6. Detects unready CRUD pods and forces a rollout restart to acquire fresh Entra tokens

Verify script completed successfully — look for Dev environment ready. at the end.

Step 0.1: Verify Core Connectivity

After the script completes, verify these endpoints respond before proceeding:

Check	Command	Expected
CRUD health	curl -s $APIM_BASE/api/health	{"status": "ok"}
CRUD readiness	curl -s $APIM_BASE/api/ready	{"status": "ready", ...} (DB + Redis + Event Hub)
Product listing	curl -s "$APIM_BASE/api/products?limit=1"	JSON array with at least 1 product
Agent health (any)	curl -s $APIM_BASE/agents/ecommerce-catalog-search/health	{"status": "ok"}

Where $APIM_BASE is resolved from:

1. azd env get-values → APIM_GATEWAY_URL (preferred)
2. Computed: https://<projectName>-<environment>-apim.azure-api.net
3. Fallback: Use the SWA proxy at https://blue-meadow-00fcb8810.4.azurestaticapps.net/api (routes through Next.js API proxy → APIM)

Step 0.2: Deep Investigation Protocol

If any pre-flight check fails, do NOT proceed to agent testing. Instead:

1. Check AKS pod status: kubectl get pods -n holiday-peak-crud --no-headers and kubectl get pods -n holiday-peak-agents --no-headers
2. Check pod logs: kubectl logs -n holiday-peak-crud deployment/crud-service-crud-service --tail=50
3. Check Event Hub connectivity: kubectl logs -n holiday-peak-agents deployment/<agent-name> --tail=30 | grep -i "event.*hub\|consumer\|partition"
4. Check Redis: kubectl exec -n holiday-peak-crud deployment/crud-service-crud-service -- python -c "import redis; r=redis.from_url('$REDIS_URL'); print(r.ping())"
5. Check Cosmos DB: verify COSMOS_ACCOUNT_URI is reachable via curl -s "$COSMOS_ACCOUNT_URI" -o /dev/null -w "%{http_code}"
6. Check APIM proxy: curl -sv $APIM_BASE/api/health 2>&1 | grep "< HTTP"
7. Re-run the recovery script if infrastructure was partially recovered
8. Document every failure with timestamp, endpoint, HTTP status, and response body before retrying

Non-Functional Requirements

Sync Agents (11 — real-time, user-facing)

Agents: ecommerce-catalog-search, ecommerce-cart-intelligence, ecommerce-checkout-support, ecommerce-order-status, ecommerce-product-detail-enrichment, crm-profile-aggregation, crm-support-assistance, inventory-reservation-validation, logistics-eta-computation, logistics-carrier-selection, logistics-returns-support.

Requirement	Target	Validation
Agent health response	< 2 seconds	GET /agents/{service}/health
Invoke response P95	< 8 seconds (5s pipeline + 3s HTTP overhead)	POST /agents/{service}/invoke
Streaming response (SSE)	First token < 3 seconds	POST /agents/{service}/invoke/stream
MCP tool call	< 5 seconds round-trip	POST /agents/{service}/mcp/{tool}
CRUD REST operations	< 500ms for reads, < 1s for writes	Standard REST calls

Async Agents (15 — background, event-driven)

Agents: crm-campaign-intelligence, crm-segmentation-personalization, inventory-alerts-triggers, inventory-health-check, inventory-jit-replenishment, logistics-route-issue-detection, product-management-acp-transformation, product-management-assortment-optimization, product-management-consistency-validation, product-management-normalization-classification, search-enrichment-agent, truth-ingestion, truth-enrichment, truth-hitl, truth-export.

Requirement	Target	Validation
Agent health response	< 2 seconds	GET /agents/{service}/health
Event Hub processing	Event consumed within 30 seconds	Check agent logs after CRUD event publish
Consumer lag	< 10 minutes behind head	Event Hubs consumer group lag metric
Throughput (batch window)	Process ≥ 95% of events per 15-min window	Log Analytics query on processed vs received
MCP tool call	< 5 seconds round-trip	POST /agents/{service}/mcp/{tool}

Note: Async agents do NOT have an invoke latency SLA. Their /invoke endpoint (if present) is used for manual testing only and is not subject to the 8-second target.

Architecture Overview

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flowchart TB
  subgraph "Public Entry Points"
    SWA["SWA Frontend<br/>(blue-meadow-*.azurestaticapps.net)"]
    APIM["APIM Gateway<br/>(*.azure-api.net)"]
  end

  subgraph "CRUD Namespace (holiday-peak-crud)"
    CRUD["CRUD Service<br/>REST endpoints"]
  end

  subgraph "Agent Namespace (holiday-peak-agents)"
    EC["eCommerce Agents (5)"]
    CRM["CRM Agents (4)"]
    INV["Inventory Agents (4)"]
    LOG["Logistics Agents (4)"]
    PM["Product Mgmt Agents (4)"]
    TL["Truth Layer (4) + Search (1)"]
  end

  subgraph "Async Backbone"
    EH_RETAIL["Event Hub<br/>(retail choreography)"]
    EH_PLATFORM["Event Hub<br/>(platform jobs)"]
  end

  subgraph "Data Tier"
    PG["PostgreSQL"]
    REDIS["Redis (Hot Memory)"]
    COSMOS["Cosmos DB (Warm Memory)"]
    BLOB["Blob Storage (Cold Memory)"]
    AIS["AI Search Index"]
  end

  SWA -->|"Next.js API proxy"| APIM
  APIM -->|"/api/*"| CRUD
  APIM -->|"/agents/{svc}/invoke"| EC & CRM & INV & LOG & PM & TL
  APIM -->|"/agents/{svc}/mcp/{tool}"| EC & CRM & INV & LOG & PM & TL
  CRUD -->|"publishes events"| EH_RETAIL
  EH_RETAIL -->|"subscriptions"| EC & CRM & INV & LOG
  EH_PLATFORM -->|"platform jobs"| TL
  CRUD --> PG
  EC & CRM & INV & LOG & PM & TL --> REDIS & COSMOS & BLOB
  TL --> AIS

Endpoint Reference

Standard Agent Endpoints (all 26 agents)

Every agent built with create_standard_app() exposes:

Endpoint	Method	Purpose
/health	GET	Liveness check
/ready	GET	Readiness (memory tiers, Foundry bindings)
/invoke	POST	Synchronous agent invocation
/invoke/stream	POST	SSE streaming invocation
/integrations	GET	List connected integrations
/self-healing/status	GET	Self-healing kernel status
/agent/traces	GET	Recent trace data
/agent/metrics	GET	Agent performance metrics
/mcp/{tool_name}	POST	MCP tool call (agent-to-agent)

APIM Routing Convention

APIM Gateway
├── /api/*                              → CRUD Service (REST)
├── /agents/{service-name}/invoke       → Agent POST /invoke
├── /agents/{service-name}/health       → Agent GET /health
├── /agents/{service-name}/mcp/{tool}   → Agent POST /mcp/{tool}
└── /agents/{service-name}/invoke/stream → Agent POST /invoke/stream

Public Endpoint Resolution

Use this priority order to determine the base URL:

1. APIM_GATEWAY_URL from azd env get-values (production-grade, direct to APIM)
2. Computed APIM URL: https://{projectName}-{env}-apim.azure-api.net
3. SWA proxy (fallback): https://blue-meadow-00fcb8810.4.azurestaticapps.net/api — routes through Next.js [...path]/route.ts → APIM

---

Testing Plan: Agent-by-Agent Behavioral Validation

Each agent is tested independently as a standalone solution. Tests are grouped by domain and graded by complexity.

Complexity Scale

Level	Label	Description
0	None	Health check, simple GET, no AI reasoning
1	Low	Single-intent query, deterministic response expected
2	Medium	Multi-attribute query, requires context aggregation
3	High	Multi-step reasoning, cross-domain, ambiguous intent

Call Type Legend

Type	Symbol	Description
HTTP Sync	[HTTP]	POST /agents/{svc}/invoke with JSON payload
HTTP Stream	[SSE]	POST /agents/{svc}/invoke/stream with SSE response
Event Hub Async	[EH]	Trigger via CRUD action that publishes to Event Hub; verify agent consumed event
MCP Tool	[MCP]	POST /agents/{svc}/mcp/{tool} structured data call
CRUD REST	[REST]	Direct CRUD REST endpoint call (supports agent testing)

---

Domain 1: eCommerce (5 agents)

1.1 ecommerce-catalog-search

APIM path: /agents/ecommerce-catalog-search

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	POST /invoke with {"query": "ping", "limit": 1, "mode": "keyword"}	Returns response with results array and mode field	HTTP 200, response < 2s
2	Low	[HTTP]	{"query": "red running shoes", "limit": 5, "mode": "intelligent"}	Returns athletic footwear results	Results contain shoe/footwear items, < 5s
3	Medium	[HTTP]	{"query": "I'm traveling to Russia next month, which clothes should I get?", "limit": 5, "mode": "intelligent"}	Intent classification identifies cold-weather clothing	result_type is not degraded_fallback, results are contextually relevant
4	Medium	[SSE]	Same as #3 but via /invoke/stream	Progressive token streaming	First token < 3s, no flash-of-full-content
5	High	[HTTP]	{"query": "I'm buying a new house, 140 square meters, I need furniture and I like modern stuff", "limit": 10, "mode": "intelligent"}	Multi-intent: furniture + modern style + size context	Sub-query fan-out, results span furniture categories
6	High	[HTTP]	{"query": "My dog ate his collar, help me out", "limit": 5, "mode": "intelligent"}	Understands implicit need (replacement pet collar)	Returns pet supplies, not random results
7	Medium	[MCP]	POST /mcp/search_products with {"query": "winter boots", "limit": 3}	Structured product results for downstream agent	Returns dict with product list
8	Low	[EH]	Create a product via POST /api/products (CRUD) → publishes product-events	catalog-search agent receives and indexes the event	Verify via agent logs or search the new product
9	High	[HTTP]	{"query": "What's the best gear for a week-long hike in the Swiss Alps?", "limit": 8, "mode": "intelligent"}	Multi-category: hiking boots, jackets, backpacks, accessories	Results span multiple categories
10	High	[HTTP]	{"query": "Help me pick a stylish but comfortable outfit for a music festival weekend", "limit": 8, "mode": "intelligent"}	Balances comfort + style, casual wear	Subjective intent handled, results are fashion-relevant

1.2 ecommerce-cart-intelligence

APIM path: /agents/ecommerce-cart-intelligence

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "What should I add to my cart?", "user_id": "test-user-1"}	Cart recommendations based on user context	Returns product suggestions
3	Medium	[HTTP]	{"query": "I have running shoes in my cart, what else do I need for marathon training?"}	Complementary product suggestions	Returns socks, water bottles, shorts, etc.
4	Medium	[MCP]	POST /mcp/get_cart_recommendations with {"user_id": "test-user-1"}	Structured recommendation payload	Dict with recommended product IDs
5	High	[HTTP]	{"query": "I'm hosting a dinner party for 8, what do I need from my cart perspective?"}	Cross-category: kitchen, dining, food, decor	Multi-domain reasoning
6	Low	[EH]	Place an order via POST /api/orders → publishes order-events	cart-intelligence receives order event and updates recommendations	Check agent logs for event processing
7	High	[HTTP]	{"query": "My budget is $200, optimize my cart for best value"}	Budget-aware filtering and prioritization	Respects price constraint
8	Medium	[EH]	Update inventory via PATCH /api/inventory/{sku} → publishes inventory-events	Agent updates cart suggestions based on stock changes	Event consumed within 30s
9	Low	[HTTP]	{"query": "Remove duplicates from my suggestions"}	De-duplication logic	No repeated products in response
10	High	[SSE]	{"query": "Compare the items in my cart and suggest upgrades for each"} via /invoke/stream	Streaming comparison analysis	Progressive tokens, structured comparison

1.3 ecommerce-checkout-support

APIM path: /agents/ecommerce-checkout-support

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Can I check out now?", "session_id": "test-session"}	Checkout eligibility assessment	Returns validation result
3	Medium	[HTTP]	{"query": "I want to split payment between two cards"}	Payment method guidance	Explains payment options or limitations
4	Medium	[MCP]	POST /mcp/validate_checkout_allocation with {"session_id": "test-session"}	Structured allocation check	Dict with allocation status per item
5	High	[HTTP]	{"query": "I have 3 items from different warehouses, what's the fastest way to get everything?"}	Multi-warehouse checkout optimization	Considers shipping consolidation
6	Low	[EH]	Reserve inventory via POST /api/inventory/reservations → publishes inventory-events	Agent validates reservation allocation	Event consumed, allocation tracked
7	High	[HTTP]	{"query": "Apply my loyalty discount, use gift card for $50, and pay the rest with credit card"}	Multi-payment-method orchestration	Handles complex payment splitting
8	Medium	[HTTP]	{"query": "One item is backordered, should I wait or ship what's available?"}	Partial fulfillment decision support	Provides options with trade-offs
9	Low	[HTTP]	{"query": "What's my order total with tax?"}	Tax calculation summary	Returns computed total
10	High	[SSE]	{"query": "Walk me through the entire checkout process step by step"} via /invoke/stream	Guided checkout walkthrough	Streaming multi-step guidance

1.4 ecommerce-order-status

APIM path: /agents/ecommerce-order-status

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Where is my order?", "order_id": "ORD-001"}	Order tracking information	Returns status and location
3	Medium	[HTTP]	{"query": "My order was supposed to arrive yesterday, what happened?"}	Delay explanation with context	Identifies delay reason
4	Medium	[MCP]	POST /mcp/get_order_tracking with {"order_id": "ORD-001"}	Structured tracking data	Dict with carrier, status, ETA
5	High	[HTTP]	{"query": "I have 5 pending orders, which one will arrive first?"}	Multi-order comparison with ETA ranking	Sorted by expected delivery
6	Low	[EH]	Trigger shipment via CRUD → publishes shipment-events	order-status agent receives shipment update	Event consumed, status updated
7	High	[HTTP]	{"query": "My package shows delivered but I never received it, what should I do?"}	Missing package resolution flow	Escalation guidance, support ticket suggestion
8	Medium	[HTTP]	{"query": "Can I change the delivery address for order ORD-001?"}	Address change feasibility check	Returns whether modification is possible
9	Low	[HTTP]	{"query": "Track order ORD-001"}	Simple tracking	Direct status response
10	High	[SSE]	{"query": "Give me a detailed timeline of everything that happened with order ORD-001"} via /invoke/stream	Full order lifecycle narrative	Streaming event history

1.5 ecommerce-product-detail-enrichment

APIM path: /agents/ecommerce-product-detail-enrichment

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Enrich product SKU-001", "entity_id": "SKU-001"}	Product detail enrichment	Returns enriched attributes
3	Medium	[HTTP]	{"query": "What attributes are missing for product SKU-001?"}	Gap analysis for product	Lists missing UCP attributes
4	Medium	[MCP]	POST /mcp/get_enrichment_metadata with {"entity_id": "SKU-001"}	Structured enrichment status	Dict with completeness score, gaps
5	High	[HTTP]	{"query": "Enrich all products in the electronics category with ACP metadata"}	Batch enrichment orchestration	Processes multiple products
6	Low	[EH]	Update product via CRUD → publishes product-events	Agent triggers enrichment pipeline	Event consumed, enrichment started
7	High	[HTTP]	{"query": "Generate SEO-optimized descriptions for all products missing them"}	Content generation with SEO focus	Produces keyword-rich descriptions
8	Medium	[HTTP]	{"query": "Compare enrichment quality between AI-generated and human-written descriptions"}	Quality comparison analysis	Confidence score comparison
9	Low	[HTTP]	{"query": "Show enrichment status for SKU-001"}	Simple status check	Returns current enrichment state
10	High	[SSE]	{"query": "Run full enrichment on SKU-001 and explain each step as you go"} via /invoke/stream	Streaming enrichment walkthrough	Progressive step-by-step output

---

Domain 2: CRM (4 agents)

2.1 crm-campaign-intelligence

APIM path: /agents/crm-campaign-intelligence

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "What campaigns are running?"}	Active campaign list	Returns campaign summaries
3	Medium	[HTTP]	{"query": "Which campaign had the best conversion rate last month?"}	Campaign performance analysis	Ranked by conversion metrics
4	Medium	[MCP]	POST /mcp/get_campaign_orchestration with {"campaign_id": "CAMP-001"}	Structured campaign data	Dict with targeting, performance, status
5	High	[HTTP]	{"query": "Design a Black Friday campaign targeting high-value customers who bought electronics last year"}	Campaign generation with segmentation	Multi-criteria targeting strategy
6	Low	[EH]	Process payment via POST /api/payments → publishes payment-events	campaign-intelligence updates campaign attribution	Event consumed, attribution tracked
7	High	[HTTP]	{"query": "Compare the ROI of email vs push notification campaigns for Q4"}	Cross-channel campaign analysis	ROI comparison with recommendations
8	Medium	[EH]	Create order via POST /api/orders → publishes order-events	Agent updates campaign metrics from order	Event consumed within 30s
9	Low	[HTTP]	{"query": "Show me campaign CAMP-001 details"}	Single campaign lookup	Returns campaign record
10	High	[SSE]	{"query": "Generate a full holiday season campaign strategy with timeline, segments, and channel allocation"} via /invoke/stream	Complex multi-step campaign plan	Streaming strategic document

2.2 crm-profile-aggregation

APIM path: /agents/crm-profile-aggregation

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Get profile for user-1"}	User profile aggregation	Returns unified profile
3	Medium	[HTTP]	{"query": "What are the purchase patterns for user-1 over the last 6 months?"}	Temporal purchase analysis	Pattern identification
4	Medium	[MCP]	POST /mcp/get_profile_context with {"user_id": "user-1"}	Structured profile context	Dict with demographics, preferences, history
5	High	[HTTP]	{"query": "Build a 360-degree customer view combining orders, support tickets, and browsing behavior"}	Cross-domain profile synthesis	Aggregates multiple data sources
6	Low	[EH]	Update user profile via PATCH /api/users/me → publishes user-events	profile-aggregation updates cached profile	Event consumed, profile refreshed
7	High	[HTTP]	{"query": "Predict churn risk for customers who haven't ordered in 90 days"}	Churn prediction analysis	Risk scores with reasoning
8	Medium	[EH]	Place order via POST /api/orders → publishes order-events	Agent incorporates new order into profile	Profile updated with latest order
9	Low	[HTTP]	{"query": "Show preferences for user-1"}	Simple preference lookup	Returns stored preferences
10	High	[SSE]	{"query": "Generate a comprehensive customer lifetime value report for user-1"} via /invoke/stream	CLV analysis with purchase history	Streaming analytical report

2.3 crm-segmentation-personalization

APIM path: /agents/crm-segmentation-personalization

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "What segments exist?"}	List of customer segments	Returns segment definitions
3	Medium	[HTTP]	{"query": "Which segment has the highest average order value?"}	Segment ranking by AOV	Ranked segment list
4	Medium	[MCP]	POST /mcp/get_segmentation with {"criteria": "high_value"}	Structured segment data	Dict with member count, criteria, metrics
5	High	[HTTP]	{"query": "Create a new segment for customers who buy both electronics and pet supplies"}	Cross-category segment creation	New segment definition with rules
6	Low	[HTTP]	{"query": "How many customers are in the VIP segment?"}	Simple count query	Returns member count
7	High	[HTTP]	{"query": "Personalize the homepage for a returning customer who browsed winter coats but didn't buy"}	Personalization strategy	Content recommendations for abandoned browse
8	Medium	[HTTP]	{"query": "Compare engagement rates between the 'new customers' and 'loyal customers' segments"}	Segment comparison analysis	Side-by-side metrics
9	Low	[HTTP]	{"query": "Show segment VIP details"}	Single segment lookup	Returns segment record
10	High	[SSE]	{"query": "Design a personalization strategy for each of our top 5 segments with channel-specific content"} via /invoke/stream	Multi-segment personalization plan	Streaming strategic output

2.4 crm-support-assistance

APIM path: /agents/crm-support-assistance

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "I need help with my order"}	Support ticket initiation	Acknowledgment with ticket ID
3	Medium	[HTTP]	{"query": "My product arrived damaged, I want a replacement"}	Damage claim processing	Returns resolution options (replace, refund)
4	Medium	[MCP]	POST /mcp/create_support_ticket with {"issue": "damaged_product", "order_id": "ORD-001"}	Structured ticket creation	Dict with ticket ID, priority, assignee
5	High	[HTTP]	{"query": "I've had 3 issues with my last 3 orders, I'm considering canceling my membership"}	Escalation with retention strategy	Identifies pattern, suggests retention actions
6	Low	[EH]	Initiate return via POST /api/returns → publishes return-events	support-assistance receives return event	Event consumed, ticket auto-created
7	High	[HTTP]	{"query": "I ordered a gift, it arrived late, and the recipient already bought the same thing. Can I return it even though it's past the window?"}	Complex exception handling	Evaluates return policy edge case
8	Medium	[HTTP]	{"query": "What's the status of my support ticket TICKET-001?"}	Ticket status inquiry	Returns ticket state and updates
9	Low	[HTTP]	{"query": "I want to speak to a human agent"}	Escalation to human	Escalation path triggered
10	High	[SSE]	{"query": "Review my entire interaction history and suggest how to prevent issues like these in the future"} via /invoke/stream	Full interaction analysis with recommendations	Streaming analytical response

---

Domain 3: Inventory (4 agents)

3.1 inventory-alerts-triggers

APIM path: /agents/inventory-alerts-triggers

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Are there any active inventory alerts?"}	Active alert list	Returns current alerts
3	Medium	[HTTP]	{"query": "Which products are below their reorder threshold?"}	Threshold breach analysis	List of products below threshold
4	Medium	[MCP]	POST /mcp/dispatch_alert with {"sku": "SKU-001", "alert_type": "low_stock"}	Structured alert dispatch	Dict with alert ID, severity, actions
5	High	[HTTP]	{"query": "Predict which products will hit zero stock in the next 7 days based on current velocity"}	Predictive stock-out analysis	Velocity-based forecasting
6	Low	[EH]	Update inventory via CRUD → publishes inventory-events	alerts-triggers evaluates threshold	Event consumed, alert generated if breached
7	High	[HTTP]	{"query": "Create an alert strategy for the holiday season with dynamic thresholds based on demand forecasts"}	Dynamic threshold planning	Season-aware alert configuration
8	Medium	[HTTP]	{"query": "Show me all alerts triggered in the last 24 hours"}	Recent alert history	Time-filtered alert list
9	Low	[HTTP]	{"query": "Check stock level for SKU-001"}	Simple stock check	Returns current stock
10	High	[SSE]	{"query": "Analyze our entire inventory alert history and recommend threshold adjustments per category"} via /invoke/stream	Category-level threshold optimization	Streaming analytical report

3.2 inventory-health-check

APIM path: /agents/inventory-health-check

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "How is our inventory health?"}	Overall health summary	Returns health metrics
3	Medium	[HTTP]	{"query": "Which categories have the worst stock turn ratio?"}	Category-level turn analysis	Ranked by efficiency
4	Medium	[MCP]	POST /mcp/get_health_metrics with {"category": "electronics"}	Structured health metrics	Dict with stock levels, turn ratio, aging
5	High	[HTTP]	{"query": "Identify dead stock across all categories and recommend clearance strategies"}	Dead stock identification + clearance plan	Multi-category analysis
6	Low	[EH]	Inventory event from CRUD → publishes inventory-events	health-check updates health metrics	Event consumed, metrics recalculated
7	High	[HTTP]	{"query": "Compare our inventory health this month vs last month and highlight the biggest changes"}	Month-over-month comparison	Trend analysis with deltas
8	Medium	[HTTP]	{"query": "What's the average days-on-hand for our top 20 selling products?"}	Days-on-hand calculation	Per-product metric
9	Low	[HTTP]	{"query": "Inventory health summary"}	Quick summary	Condensed health report
10	High	[SSE]	{"query": "Generate a full inventory health report with recommendations for Q1 planning"} via /invoke/stream	Comprehensive health report	Streaming analytical output

3.3 inventory-jit-replenishment

APIM path: /agents/inventory-jit-replenishment

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "What needs to be reordered?"}	Reorder recommendations	Returns items needing replenishment
3	Medium	[HTTP]	{"query": "Calculate optimal reorder quantities for electronics category"}	Category-specific reorder plan	Quantities based on velocity and lead time
4	Medium	[MCP]	POST /mcp/get_replenishment_plan with {"sku": "SKU-001"}	Structured replenishment data	Dict with quantity, supplier, lead time
5	High	[HTTP]	{"query": "Design a just-in-time replenishment strategy for the holiday peak season, considering 3x normal demand"}	Peak season JIT strategy	Demand multiplier + supplier capacity
6	Low	[EH]	Order placed via POST /api/orders → publishes order-events	JIT recalculates replenishment needs	Event consumed, reorder quantities updated
7	High	[HTTP]	{"query": "One of our suppliers has a 2-week delay, redistribute orders across alternative suppliers"}	Supplier disruption response	Multi-supplier rebalancing
8	Medium	[EH]	Inventory update → publishes inventory-events	JIT adjusts replenishment based on new stock levels	Event consumed within 30s
9	Low	[HTTP]	{"query": "What's the reorder point for SKU-001?"}	Simple reorder point lookup	Returns calculated ROP
10	High	[SSE]	{"query": "Generate a 30-day replenishment forecast for all categories considering seasonal demand patterns"} via /invoke/stream	Multi-category forecast	Streaming forecast report

3.4 inventory-reservation-validation

APIM path: /agents/inventory-reservation-validation

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Validate reservation RES-001"}	Reservation validation	Returns validation status
3	Medium	[HTTP]	{"query": "Are there any expired reservations that need cleanup?"}	Reservation audit	Lists stale reservations
4	Medium	[MCP]	POST /mcp/check_reservation with {"reservation_id": "RES-001"}	Structured reservation check	Dict with status, expiry, allocated quantity
5	High	[HTTP]	{"query": "We have 50 units of SKU-001 but 60 units reserved across all checkouts, resolve the over-reservation"}	Over-reservation conflict resolution	Priority-based allocation strategy
6	Low	[EH]	Create reservation via POST /api/inventory/reservations → publishes inventory-events	Agent validates the reservation	Event consumed, validation performed
7	High	[HTTP]	{"query": "Analyze reservation patterns and identify products that consistently over-reserve"}	Reservation pattern analysis	Historical over-reservation trends
8	Medium	[HTTP]	{"query": "How many active reservations do we have, and what's the total committed quantity?"}	Reservation summary metrics	Aggregated counts
9	Low	[HTTP]	{"query": "Release reservation RES-001"}	Simple release	Confirmation of release
10	High	[SSE]	{"query": "Model the impact of reducing reservation TTL from 30 to 15 minutes on stock availability"} via /invoke/stream	TTL impact simulation	Streaming analysis

---

Domain 4: Logistics (4 agents)

4.1 logistics-carrier-selection

APIM path: /agents/logistics-carrier-selection

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Which carrier should I use for a package to São Paulo?"}	Carrier recommendation	Returns ranked carriers
3	Medium	[HTTP]	{"query": "Compare FedEx vs DHL for international shipment of fragile electronics, 2kg"}	Multi-criteria carrier comparison	Cost, speed, reliability comparison
4	Medium	[MCP]	POST /mcp/get_carrier_routing with {"destination": "São Paulo, Brazil", "weight_kg": 2}	Structured carrier data	Dict with carrier options, costs, ETAs
5	High	[HTTP]	{"query": "Optimize carrier selection for 500 holiday orders going to 12 different countries, minimize cost while ensuring delivery before December 24"}	Bulk carrier optimization	Multi-destination, deadline-constrained routing
6	Low	[EH]	CRUD publishes shipment-events on shipment creation	carrier-selection receives shipment	Event consumed, carrier assigned
7	High	[HTTP]	{"query": "A carrier just announced a strike, reroute all pending shipments to alternatives"}	Emergency carrier rerouting	Disruption handling with alternatives
8	Medium	[HTTP]	{"query": "What's the cheapest carrier for next-day delivery within the US?"}	Filtered carrier search	Cost-optimized with speed constraint
9	Low	[HTTP]	{"query": "List available carriers for domestic shipments"}	Simple carrier list	Returns domestic carriers
10	High	[SSE]	{"query": "Generate a carrier performance report for last quarter with recommendations for contract renegotiation"} via /invoke/stream	Carrier performance analytics	Streaming performance report

4.2 logistics-eta-computation

APIM path: /agents/logistics-eta-computation

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "ETA for shipment SHIP-001"}	Delivery estimate	Returns computed ETA
3	Medium	[HTTP]	{"query": "If I order now, when will it arrive in São Paulo considering customs clearance?"}	ETA with customs factor	Includes customs delay estimate
4	Medium	[MCP]	POST /mcp/calculate_eta with {"shipment_id": "SHIP-001"}	Structured ETA data	Dict with ETA, confidence, factors
5	High	[HTTP]	{"query": "Compute ETAs for 100 pending shipments and flag any that won't meet their promised delivery date"}	Batch ETA with SLA risk	At-risk shipments highlighted
6	Low	[EH]	Shipment event published to shipment-events	ETA agent receives and computes estimate	Event consumed, ETA calculated
7	High	[HTTP]	{"query": "A hurricane is approaching the Southeast US, recalculate all ETAs for affected shipments"}	Weather-disruption ETA adjustment	Revised ETAs with weather factor
8	Medium	[EH]	Order placed via POST /api/orders → publishes order-events	ETA pre-computed for new order	Event consumed, initial ETA set
9	Low	[HTTP]	{"query": "Average delivery time to New York?"}	Simple average lookup	Returns historical average
10	High	[SSE]	{"query": "Analyze delivery performance trends over the last 6 months and predict next month's on-time rate"} via /invoke/stream	Delivery trend analysis	Streaming predictive report

4.3 logistics-returns-support

APIM path: /agents/logistics-returns-support

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "I want to return my order"}	Return initiation	Returns process and label info
3	Medium	[HTTP]	{"query": "What's the most cost-effective return method for a large furniture item?"}	Return logistics optimization	Considers item size and carrier options
4	Medium	[MCP]	POST /mcp/get_return_logistics with {"return_id": "RET-001"}	Structured return logistics	Dict with carrier, label, pickup schedule
5	High	[HTTP]	{"query": "Process 50 returns from a product recall, optimize reverse logistics for warehouse sorting"}	Batch recall return processing	Multi-item reverse logistics plan
6	Low	[EH]	Return initiated via POST /api/returns → publishes return-events	returns-support processes return logistics	Event consumed, return routed
7	High	[HTTP]	{"query": "Customer is in a remote area with no carrier pickup, suggest alternative return methods"}	Non-standard return handling	Drop-off locations, postal service alternatives
8	Medium	[HTTP]	{"query": "Track return RET-001 from customer to warehouse"}	Return tracking	Returns current location and status
9	Low	[HTTP]	{"query": "Generate return label for order ORD-001"}	Label generation	Returns label data/URL
10	High	[SSE]	{"query": "Analyze our return rates by category and recommend packaging improvements to reduce damage-related returns"} via /invoke/stream	Return analytics with recommendations	Streaming analytical report

4.4 logistics-route-issue-detection

APIM path: /agents/logistics-route-issue-detection

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Any route issues today?"}	Active route issue list	Returns current issues
3	Medium	[HTTP]	{"query": "Shipment SHIP-001 hasn't moved in 48 hours, is there a route problem?"}	Stale shipment analysis	Identifies potential route issue
4	Medium	[MCP]	POST /mcp/detect_route_anomaly with {"shipment_id": "SHIP-001"}	Structured anomaly detection	Dict with anomaly type, severity, recommendation
5	High	[HTTP]	{"query": "Detect all shipments currently stuck at a specific hub and recommend rerouting options"}	Hub bottleneck detection	Identifies congestion, suggests alternatives
6	Low	[EH]	Shipment event via shipment-events	Agent monitors for route anomalies	Event consumed, anomaly check performed
7	High	[HTTP]	{"query": "A bridge collapse has blocked Route 95, identify all affected shipments and reroute them"}	Infrastructure disruption response	Mass rerouting with impact assessment
8	Medium	[HTTP]	{"query": "Show me the top 5 route issues by severity this week"}	Weekly issue summary	Ranked by severity
9	Low	[HTTP]	{"query": "Check route for shipment SHIP-001"}	Simple route check	Returns route status
10	High	[SSE]	{"query": "Build a route reliability heat map across all our shipping corridors"} via /invoke/stream	Corridor reliability analysis	Streaming geographical analysis

---

Domain 5: Product Management (4 agents)

5.1 product-management-acp-transformation

APIM path: /agents/product-management-acp-transformation

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Transform product SKU-001 to ACP format"}	ACP transformation	Returns ACP-formatted product
3	Medium	[HTTP]	{"query": "What ACP fields are missing for products in the electronics category?"}	Category-level ACP gap analysis	Lists missing fields per product
4	Medium	[MCP]	POST /mcp/transform_to_acp with {"entity_id": "SKU-001"}	Structured ACP transformation	Dict with ACP attributes
5	High	[HTTP]	{"query": "Batch transform all 200 products to ACP format, prioritizing products with the most gaps"}	Prioritized batch transformation	Processes in gap-severity order
6	Low	[EH]	Product update via CRUD → publishes product-events	Agent triggers ACP transformation	Event consumed, transformation started
7	High	[HTTP]	{"query": "The ACP schema for apparel just changed, identify all products that need re-transformation"}	Schema migration impact analysis	Lists affected products
8	Medium	[HTTP]	{"query": "Compare ACP completeness across all categories"}	Cross-category completeness	Category-level metrics
9	Low	[HTTP]	{"query": "ACP status for SKU-001"}	Simple status check	Returns transformation state
10	High	[SSE]	{"query": "Generate an ACP readiness report for marketplace onboarding"} via /invoke/stream	Marketplace readiness assessment	Streaming compliance report

5.2 product-management-assortment-optimization

APIM path: /agents/product-management-assortment-optimization

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "How is our product assortment?"}	Assortment overview	Returns assortment metrics
3	Medium	[HTTP]	{"query": "Which categories are over-represented and which are under-represented?"}	Category balance analysis	Identifies gaps and overlaps
4	Medium	[MCP]	POST /mcp/get_assortment_analytics with {"category": "electronics"}	Structured assortment data	Dict with SKU count, depth, breadth
5	High	[HTTP]	{"query": "Optimize our assortment for the holiday season based on last year's sales data and trending items"}	Season-aware assortment optimization	Add/remove/rebalance recommendations
6	Low	[EH]	Product event from CRUD → publishes product-events	Agent updates assortment analytics	Event consumed, metrics recalculated
7	High	[HTTP]	{"query": "We're entering the pet supplies market, design an initial assortment with 50 SKUs"}	New category assortment design	Brand, price, and feature diversity plan
8	Medium	[HTTP]	{"query": "Show me the top 10 products cannibalizing each other's sales"}	Cannibalization analysis	Product pairs with overlap
9	Low	[HTTP]	{"query": "How many SKUs do we have in electronics?"}	Simple count	Returns SKU count
10	High	[SSE]	{"query": "Create a full assortment strategy for next fiscal year with budget allocation by category"} via /invoke/stream	Annual assortment plan	Streaming strategic document

5.3 product-management-consistency-validation

APIM path: /agents/product-management-consistency-validation

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Validate consistency for SKU-001"}	Consistency validation	Returns validation result
3	Medium	[HTTP]	{"query": "Find all products with inconsistent pricing between retail and wholesale channels"}	Cross-channel price consistency	Lists pricing mismatches
4	Medium	[MCP]	POST /mcp/check_consistency with {"entity_id": "SKU-001"}	Structured consistency check	Dict with violations, severity
5	High	[HTTP]	{"query": "Run a full consistency audit across all product data, including image URLs, descriptions, and attribute completeness"}	Full catalog consistency audit	Multi-dimension validation
6	Low	[EH]	completeness-jobs event from truth-ingestion	Agent runs consistency check on new data	Event consumed, validation performed
7	High	[HTTP]	{"query": "Products imported from the ERP have different naming conventions, normalize and validate all imported products"}	Import normalization + validation	Identifies and fixes naming inconsistencies
8	Medium	[HTTP]	{"query": "Show me the top consistency issues by category"}	Category-level issue ranking	Ranked violations
9	Low	[HTTP]	{"query": "Is SKU-001 consistent?"}	Simple boolean check	Returns pass/fail
10	High	[SSE]	{"query": "Generate a data quality scorecard for the entire catalog with remediation priorities"} via /invoke/stream	Quality scorecard	Streaming quality report

5.4 product-management-normalization-classification

APIM path: /agents/product-management-normalization-classification

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Classify product SKU-001"}	Product classification	Returns category/subcategory
3	Medium	[HTTP]	{"query": "We have 20 products with missing categories, auto-classify them based on their descriptions"}	Batch auto-classification	Category assignment with confidence
4	Medium	[MCP]	POST /mcp/normalize_product with {"entity_id": "SKU-001"}	Structured normalization	Dict with normalized attributes
5	High	[HTTP]	{"query": "Reclassify our entire catalog using the new taxonomy that splits 'electronics' into 'computers', 'mobile', 'home electronics', and 'accessories'"}	Taxonomy migration	Mass reclassification with mapping
6	Low	[EH]	Product event from CRUD → publishes product-events	Agent normalizes and classifies new product	Event consumed, classification applied
7	High	[HTTP]	{"query": "Products from our new supplier use a different attribute schema, map their fields to our standard and normalize values"}	Schema mapping + normalization	Cross-schema attribute mapping
8	Medium	[HTTP]	{"query": "Show me products with low classification confidence that need human review"}	Low-confidence queue	Products needing manual review
9	Low	[HTTP]	{"query": "What category is SKU-001 in?"}	Simple lookup	Returns current category
10	High	[SSE]	{"query": "Analyze classification accuracy across all categories and recommend taxonomy improvements"} via /invoke/stream	Taxonomy quality analysis	Streaming analytical output

---

Domain 6: Truth Layer + Search (5 agents)

6.1 truth-ingestion

APIM path: /agents/truth-ingestion

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /ingest/bulk with JSON array of products	Bulk ingestion	Returns ingestion receipt with count
3	Medium	[HTTP]	POST /ingest/bulk with 50+ products, mixed quality	Ingestion with validation	Rejects malformed, accepts valid
4	Medium	[HTTP]	{"query": "Ingest product from connector webhook", "source": "erp"}	Connector-sourced ingestion	Handles ERP format transformation
5	High	[HTTP]	Ingest 200 products from CSV → verify downstream completeness-jobs events fire	Full pipeline trigger	truth-ingestion → completeness-jobs → consistency-validation
6	Low	[HTTP]	POST /ingest/bulk with 1 product	Single item ingestion	Event published to completeness-jobs
7	High	[HTTP]	Ingest products with intentionally incomplete data → verify gap detection	Incomplete data handling	Gaps identified, scored, routed
8	Medium	[HTTP]	Re-ingest same product → verify idempotency	Idempotent re-ingestion	No duplicates, updated timestamps
9	Low	[HTTP]	GET /ready	Readiness check	Returns ready status
10	High	[HTTP]	Ingest products spanning all 11 categories → verify category-specific schemas applied	Multi-category ingestion	Per-category UCP schema binding

6.2 truth-enrichment

APIM path: /agents/truth-enrichment

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[EH]	Publish enrichment-jobs event for one product	Single product enrichment	Agent processes and writes proposed attributes
3	Medium	[EH]	Publish enrichment-jobs for product with 5+ attribute gaps	Multi-gap enrichment	Each gap filled with confidence score
4	Medium	[HTTP]	POST /invoke with {"query": "Enrich product SKU-001"}	Direct enrichment invocation	Returns enrichment result
5	High	[EH]	Publish 20 enrichment-jobs events simultaneously	Concurrent batch processing	All 20 processed within 2 minutes
6	Low	[EH]	Publish event for product with all attributes present	No-gap enrichment	Agent detects no gaps, marks complete
7	High	[EH]	Enrich product with low-confidence results → verify hitl-jobs event fires	HITL routing	Low confidence (< 0.95) routes to HITL
8	Medium	[HTTP]	Query enrichment status for a previously enriched product	Enrichment status check	Returns proposed attributes + confidence
9	Low	[HTTP]	GET /ready	Readiness check	Returns ready status
10	High	[EH]	Full pipeline: enrichment → search-enrichment-jobs event → search agent indexes	End-to-end bridge	truth-enrichment → search-enrichment-agent chain

6.3 truth-hitl

APIM path: /agents/truth-hitl

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Show pending reviews"}	Review queue	Returns items awaiting HITL review
3	Medium	[HTTP]	{"query": "Approve all proposed attributes for SKU-001 with confidence > 0.90"}	Conditional batch approval	Approves qualifying attributes
4	Medium	[EH]	hitl-jobs event from truth-enrichment	Agent queues item for review	Event consumed, item in review queue
5	High	[HTTP]	{"query": "Review all pending items, auto-approve those above 0.90 confidence, flag the rest for human review with reasons"}	Smart review triage	Two-tier decision making
6	Low	[HTTP]	POST /invoke with {"query": "How many items are in the review queue?"}	Queue depth	Returns pending count
7	High	[HTTP]	{"query": "For the rejected attributes, explain why each was rejected and suggest improvements"}	Rejection analysis	Detailed feedback per rejection
8	Medium	[HTTP]	{"query": "Show me the items that have been in the queue longest"}	Queue aging	Sorted by wait time
9	Low	[HTTP]	GET /ready	Readiness check	Returns ready status
10	High	[SSE]	{"query": "Generate a HITL reviewer productivity report with approval rates, average review time, and quality metrics"} via /invoke/stream	Reviewer performance analytics	Streaming report

6.4 truth-export

APIM path: /agents/truth-export

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[HTTP]	POST /invoke with {"query": "Export approved truth for SKU-001"}	Single product export	Returns export payload
3	Medium	[HTTP]	{"query": "Export all approved products in the electronics category as CSV"}	Category-filtered bulk export	CSV output with approved attributes
4	Medium	[HTTP]	{"query": "Export to blob storage for downstream consumption"}	Blob export	Data written to cold storage
5	High	[HTTP]	{"query": "Export all approved truth data, push to AI Search index, and writeback to PIM system"}	Multi-destination export	Blob + AI Search + PIM writeback
6	Low	[HTTP]	POST /invoke with {"query": "Export status"}	Export status	Returns last export metadata
7	High	[HTTP]	{"query": "Incremental export: only products approved since last export run"}	Delta export	Timestamp-based filtering
8	Medium	[HTTP]	{"query": "Validate exported data against UCP schema before publishing"}	Pre-export validation	Schema compliance check
9	Low	[HTTP]	GET /ready	Readiness check	Returns ready status
10	High	[SSE]	{"query": "Run full export pipeline with progress tracking and error reporting for each destination"} via /invoke/stream	Full export with real-time progress	Streaming progress report

6.5 search-enrichment-agent

APIM path: /agents/search-enrichment-agent

#	Complexity	Type	Prompt / Action	Expected Behavior	Validation
1	None	[HTTP]	GET /health	Health OK	HTTP 200
2	Low	[EH]	Publish search-enrichment-jobs event for one product	Single product search enrichment	use_cases, keywords, enriched_description generated
3	Medium	[EH]	Publish event for complex product (long description, many features)	Complex enrichment	Model-assisted enrichment path used
4	Medium	[HTTP]	POST /invoke with {"query": "Enrich SKU-001 for search"}	Direct search enrichment	Returns enriched search fields
5	High	[EH]	Publish 10 events → verify all appear in AI Search index	Batch indexing	All products queryable via hybrid search
6	Low	[EH]	Publish event for simple product (short description)	Deterministic enrichment	Fast path, no model call
7	High	[EH]	Enrich product → query via catalog-search → verify enriched fields improve results	End-to-end search quality	Better results with enrichment vs without
8	Medium	[HTTP]	{"query": "Show enrichment status for SKU-001"}	Enrichment status	Returns enriched fields and scores
9	Low	[HTTP]	GET /ready	Readiness check	Returns ready status
10	High	[EH]	Re-enrich product with updated truth data → verify AI Search index updated	Re-enrichment + index update	Index reflects latest enriched data

---

Cross-Domain Integration Tests

After individual agent validation, run these cross-domain scenarios that exercise the full choreography:

#	Scenario	Agents Involved	Trigger	Verification
1	Customer Order Flow	cart-intelligence → checkout-support → CRUD orders → order-status → carrier-selection → eta-computation	POST /api/cart/items → POST /api/checkout/sessions → POST /api/orders	Order created, carrier assigned, ETA computed
2	Product Enrichment Pipeline	truth-ingestion → truth-enrichment → truth-hitl → truth-export → search-enrichment → catalog-search	CSV upload to truth-ingestion	Product searchable via intelligent search
3	Inventory Alert Chain	CRUD inventory update → alerts-triggers → jit-replenishment → health-check	PATCH /api/inventory/{sku} (set stock to 1)	Alert generated, replenishment calculated, health updated
4	Return Processing Flow	CRUD returns → support-assistance → returns-support → inventory update	POST /api/returns	Return processed, logistics arranged, stock updated
5	Campaign Attribution Loop	CRUD order → campaign-intelligence → profile-aggregation → segmentation-personalization	POST /api/orders	Campaign attribution updated, profile refreshed, segment recalculated

Execution Workflow

Phase 1: Infrastructure (mandatory, 5-10 min)

# Step 1: Recover infrastructure
./scripts/start-dev-environment.ps1

# Step 2: Resolve APIM base URL
$azdVars = azd env get-values | ConvertFrom-StringData
$APIM_BASE = if ($azdVars.APIM_GATEWAY_URL) { $azdVars.APIM_GATEWAY_URL.TrimEnd('/') } else { "https://holidaypeakhub405-dev-apim.azure-api.net" }

# Step 3: Verify core connectivity
curl -s "$APIM_BASE/api/health"
curl -s "$APIM_BASE/api/ready"
curl -s "$APIM_BASE/api/products?limit=1"

Phase 2: Agent Health Sweep (2-3 min)

Run health checks on all 26 agents:

$agents = @(
  "ecommerce-cart-intelligence", "ecommerce-catalog-search", "ecommerce-checkout-support",
  "ecommerce-order-status", "ecommerce-product-detail-enrichment",
  "crm-campaign-intelligence", "crm-profile-aggregation",
  "crm-segmentation-personalization", "crm-support-assistance",
  "inventory-alerts-triggers", "inventory-health-check",
  "inventory-jit-replenishment", "inventory-reservation-validation",
  "logistics-carrier-selection", "logistics-eta-computation",
  "logistics-returns-support", "logistics-route-issue-detection",
  "product-management-acp-transformation", "product-management-assortment-optimization",
  "product-management-consistency-validation", "product-management-normalization-classification",
  "search-enrichment-agent",
  "truth-ingestion", "truth-enrichment", "truth-hitl", "truth-export"
)

foreach ($agent in $agents) {
    $url = "$APIM_BASE/agents/$agent/health"
    try {
        $resp = Invoke-RestMethod -Uri $url -TimeoutSec 5
        Write-Host "[OK] $agent" -ForegroundColor Green
    } catch {
        Write-Host "[FAIL] $agent - $($_.Exception.Message)" -ForegroundColor Red
    }
}

Phase 3: Domain-by-Domain Testing (30-60 min)

Execute the testing plan tables above, domain by domain:

1. eCommerce (5 agents × 10 prompts = 50 tests)
2. CRM (4 agents × 10 prompts = 40 tests)
3. Inventory (4 agents × 10 prompts = 40 tests)
4. Logistics (4 agents × 10 prompts = 40 tests)
5. Product Management (4 agents × 10 prompts = 40 tests)
6. Truth Layer + Search (5 agents × 10 prompts = 50 tests)

Total: 260 individual test cases

Phase 4: Cross-Domain Integration (15-20 min)

Execute the 5 cross-domain integration scenarios listed above.

Phase 5: Results Summary

For each agent, record:

Agent	Health	Invoke (sync)	Stream (SSE)	MCP	Event Hub	Notes
ecommerce-catalog-search	OK/FAIL	latency_ms	first_token_ms	OK/FAIL	consumed_s
...

Quality Gate Checklist

• Infrastructure recovery script completed successfully
• All 26 agents respond to /health within 2 seconds
• CRUD /api/ready reports all subsystems healthy (DB, Redis, Event Hub)
• At least 1 product exists in the catalog (/api/products?limit=1)
• All "None" complexity tests pass (basic health/connectivity)
• All "Low" complexity tests return valid responses within SLA
• All "Medium" complexity tests demonstrate context awareness
• All "High" complexity tests demonstrate multi-step reasoning
• At least 3 Event Hub async chains verified end-to-end
• At least 2 MCP tool calls verified per domain
• At least 2 SSE streaming responses verified (first token < 3s)
• All 5 cross-domain integration scenarios completed
• No degraded_fallback responses from catalog-search
• Results summary table completed for all agents
• All failures documented with timestamp, endpoint, status, and response body

Investigation Playbook

When a test fails, follow this escalation path:

Level 1: Surface Diagnostics (1-2 min)

# Check pod status
kubectl get pods -n holiday-peak-agents -l app={agent-name}
# Check recent logs
kubectl logs -n holiday-peak-agents deployment/{agent-name} --tail=30
# Check APIM proxy
curl -sv "$APIM_BASE/agents/{agent-name}/health" 2>&1 | grep "< HTTP"

Level 2: Dependency Diagnosis (3-5 min)

# Check Foundry connectivity
kubectl logs -n holiday-peak-agents deployment/{agent-name} --tail=50 | grep -i "foundry\|model\|timeout"
# Check memory tier connectivity
kubectl logs -n holiday-peak-agents deployment/{agent-name} --tail=50 | grep -i "redis\|cosmos\|blob"
# Check Event Hub consumer
kubectl logs -n holiday-peak-agents deployment/{agent-name} --tail=50 | grep -i "event.*hub\|partition\|consumer"

Level 3: Deep Investigation (5-15 min)

# Full pod describe (events, resource limits, scheduling)
kubectl describe pod -n holiday-peak-agents -l app={agent-name}
# Resource utilization
kubectl top pods -n holiday-peak-agents -l app={agent-name}
# Network connectivity test
kubectl exec -n holiday-peak-agents deployment/{agent-name} -- python -c "import httpx; print(httpx.get('http://crud-service.holiday-peak-crud.svc.cluster.local:8000/api/health').status_code)"
# Self-healing kernel status
curl -s "$APIM_BASE/agents/{agent-name}/self-healing/status"

Level 4: Infrastructure Recovery

If multiple agents fail, return to the Pre-Flight Infrastructure Recovery section and re-run the full recovery script. If the issue persists after recovery, check:

1. AKS node pool health: kubectl get nodes
2. PostgreSQL state: az postgres flexible-server show -g $RG -n $PG --query "state"
3. Event Hub namespace health: Azure Portal → Event Hubs → Activity log
4. APIM health: Azure Portal → APIM → API health