[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[User] {"tick":48,"episode_id":"c3ca0bae-ce06-444e-a8a4-ba78e58a0e8e","task_id":"hard","status":"playing","max_steps":50,"global_slo_score":0.7826,"observation_summary":"Tick 48/50: SLO compliance 78% (1 service(s) DOWN, 3 CRITICAL, 1 degraded, 18 healthy). 23 services total.","services":[{"id":"api-gateway-east","layer":"edge","status":"degraded","error_rate":0.0405,"latency_p50_ms":1559.4,"latency_p95_ms":3162.6,"latency_p99_ms":4801.4,"throughput_rps":10153.8,"cpu_pct":15.0,"memory_pct":30.0,"connection_pool_usage_pct":10.0,"replicas":2,"version":"v1.0.0","previous_version":null,"depends_on":["auth-service-east","notification-service-east","refund-service-east","payment-service-east","order-service-east","search-service-east"],"circuit_breakers":{"auth-service-east":"CLOSED","notification-service-east":"CLOSED","refund-service-east":"CLOSED","payment-service-east":"CLOSED","order-service-east":"CLOSED","search-service-east":"OPEN"}},{"id":"auth-service-east","layer":"identity","status":"healthy","error_rate":0.0,"latency_p50_ms":20.0,"latency_p95_ms":50.0,"latency_p99_ms":100.0,"throughput_rps":50.0,"cpu_pct":15.0,"memory_pct":30.0,"connection_pool_usage_pct":10.0,"replicas":2,"version":"v1.0.0","previous_version":null,"depends_on":[],"circuit_breakers":{}}],"alerts":[{"severity":"critical","service":"search-service-east","type":"error_rate_high","message":"search-service-east error rate at 90%","first_seen_tick":0},{"severity":"critical","service":"search-service-east","type":"service_down","message":"search-service-east is DOWN","first_seen_tick":0},{"severity":"critical","service":"api-gateway-west","type":"latency_high","message":"api-gateway-west p99 latency 5158ms","first_seen_tick":48},{"severity":"critical","service":"inventory-service-west","type":"error_rate_high","message":"inventory-service-west error rate at 63%","first_seen_tick":0},{"severity":"warning","service":"api-gateway-east","type":"latency_high","message":"api-gateway-east p99 latency elevated at 4801ms","first_seen_tick":48},{"severity":"warning","service":"api-gateway-east","type":"circuit_breaker_open","message":"api-gateway-east circuit breaker OPEN for search-service-east","first_seen_tick":48}],"recent_deploys":[],"actions_taken":[],"legal_actions":[{"action_type":"noop","valid_targets":[]},{"action_type":"inspect_logs","valid_targets":["api-gateway-east","auth-service-east","notification-service-east","refund-service-east","payment-service-east","order-service-east","search-service-east","postgres-replica-east","redis-cache-east","api-gateway-west","auth-service-west","checkout-service-west","recommendation-service-west","cart-service-west","inventory-service-west","postgres-replica-west","redis-cache-west","postgres-primary","kafka-broker","config-service","metrics-collector","sms-service","rate-limiter"]},{"action_type":"inspect_metrics","valid_targets":["api-gateway-east","auth-service-east","notification-service-east","refund-service-east","payment-service-east","order-service-east","search-service-east","postgres-replica-east","redis-cache-east","api-gateway-west","auth-service-west","checkout-service-west","recommendation-service-west","cart-service-west","inventory-service-west","postgres-replica-west","redis-cache-west","postgres-primary","kafka-broker","config-service","metrics-collector","sms-service","rate-limiter"]},{"action_type":"inspect_traces","valid_targets":["api-gateway-east","auth-service-east","notification-service-east","refund-service-east","payment-service-east","order-service-east","search-service-east","postgres-replica-east","redis-cache-east","api-gateway-west","auth-service-west","checkout-service-west","recommendation-service-west","cart-service-west","inventory-service-west","postgres-replica-west","redis-cache-west","postgres-primary","kafka-broker","config-service","metrics-collector","sms-service","rate-limiter"]},{"action_type":"restart_service","valid_targets":["api-gateway-east","auth-service-east","notification-service-east","refund-service-east","payment-service-east","order-service-east","search-service-east","postgres-replica-east","redis-cache-east","api-gateway-west","auth-service-west","checkout-service-west","recommendation-service-west","cart-service-west","inventory-service-west","postgres-replica-west","redis-cache-west","postgres-primary","kafka-broker","config-service","metrics-collector","sms-service","rate-limiter"]},{"action_type":"rollback_service","valid_targets":["recommendation-service-west"]},{"action_type":"scale_service","valid_targets":["api-gateway-east","auth-service-east","notification-service-east","refund-service-east","payment-service-east","order-service-east","search-service-east","postgres-replica-east","redis-cache-east","api-gateway-west","auth-service-west","checkout-service-west","recommendation-service-west","cart-service-west","inventory-service-west","postgres-replica-west","redis-cache-west","postgres-primary","kafka-broker","config-service","metrics-collector","sms-service","rate-limiter"]},{"action_type":"tune_config","valid_targets":["api-gateway-east","auth-service-east","notification-service-east","refund-service-east","payment-service-east","order-service-east","search-service-east","postgres-replica-east","redis-cache-east","api-gateway-west","auth-service-west","checkout-service-west","recommendation-service-west","cart-service-west","inventory-service-west","postgres-replica-west","redis-cache-west","postgres-primary","kafka-broker","config-service","metrics-collector","sms-service","rate-limiter"]},{"action_type":"clear_cache","valid_targets":["redis-cache-east","redis-cache-west"]},{"action_type":"rebalance_traffic","valid_targets":["us-east-1","us-west-2"]},{"action_type":"pause_job","valid_targets":["kafka-broker"]}],"logs":null,"metric_history":null,"traces":null}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}


[System]
You are an expert Site Reliability Engineer (SRE) responding to a production incident.
You are managing a microservice cluster experiencing failures.

Your goal: restore all services to healthy SLO compliance as efficiently as possible.

Strategy:
1. First, inspect logs of services showing the highest error rates or critical alerts
2. Diagnose the root cause from log patterns:
   - OOMKilled/CrashLoopBackOff -> restart_service
   - NullPointerException/TypeError + recent deploy -> rollback_service
   - "Configuration diagnostic: key '<KEY>'" -> tune_config with that exact key, value='correct'
   - Thread pool exhaustion on THIS service -> restart_service or scale_service on THIS service
   - Memory climbing linearly -> restart_service (resource leak)
   - HikariPool exhaustion/slow queries -> scale_service or restart_service on the DB
   - CLUSTERDOWN/cache miss -> clear_cache
   - DNS/network errors -> rebalance_traffic (if multi-region)
3. Apply the correct remediation action
4. Verify recovery with inspect_logs or inspect_metrics

Respond with EXACTLY one JSON object — no explanation, no markdown, just raw JSON:
{"action_type": "...", "params": {...}}

Param rules (STRICT — single service only, never a list):
- inspect_logs / inspect_metrics / inspect_traces / restart_service / rollback_service / scale_service:
    {"action_type": "X", "params": {"service_id": "order-service"}}
- tune_config:
    {"action_type": "tune_config", "params": {"service_id": "order-service", "key": "api_endpoint", "value": "correct"}}
- clear_cache:
    {"action_type": "clear_cache", "params": {"cache_name": "redis-cache"}}
- rebalance_traffic:
    {"action_type": "rebalance_traffic", "params": {"from_region": "us-east-1", "to_region": "us-west-2"}}
- noop:
    {"action_type": "noop", "params": {}}

[Assistant] {"action_type": "noop", "params": {}}