Investigate Stuck Messages

Query the relayer API to investigate stuck messages, their retry counts, and error reasons.

When to Use

1. Alert-based triggers:

   • Alert: "Known app context relayer queue length > 0 for 40m"
   • Any alert mentioning stuck messages in prepare queue
   • High retry counts for specific app contexts

2. User request triggers:

   • "Why are messages stuck for [app_context]?"
   • "Investigate stuck messages on [chain]"
   • "What's causing the queue alert?"
   • Pasting a Grafana alert URL

Input Parameters

Option 1: Grafana Alert URL (recommended)

/investigate-stuck-messages https://abacusworks.grafana.net/alerting/grafana/cdg1ro5hi4vswb/view?tab=instances

Option 2: Manual specification

/investigate-stuck-messages app_context=EZETH/renzo-prod remote=linea

alert_url

app_context

EZETH/renzo-prod

oUSDT/production

remote

linea

ethereum

arbitrum

environment

mainnet3

*Either

alert_url

app_context

remote

Workflow

Step 1: Parse Input and Extract Alert Instances

If Grafana alert URL provided:

1. Extract the alert UID from the URL (e.g.,

   cdg1ro5hi4vswb

   from

   .../alerting/grafana/cdg1ro5hi4vswb/view

   )

2. Query Prometheus directly for firing instances using

   mcp__grafana__query_prometheus

   :

   sum by (app_context, remote)(
       max_over_time(
           hyperlane_submitter_queue_length{
               queue_name="prepare_queue",
               app_context!~"Unknown|merkly_eth|merkly_erc20|helloworld|velo_message_module",
               hyperlane_context!~"rc|vanguard0|vanguard1|vanguard2|vanguard3|vanguard4|vanguard5",
               operation_status!~"Retry\\(ApplicationReport\\(.*\\)\\)|FirstPrepareAttempt",
               hyperlane_deployment="mainnet3",
           }[2m]
       )
   ) > 0
   

3. Extract

   app_context

   and

   remote

   labels from each result.

If manual app_context/remote provided:

Use the provided values directly.

Step 2: Setup Port-Forward to Relayer

Check if port 9090 is already in use:

lsof -i :9090

If not in use, start port-forward in background:

kubectl port-forward omniscient-relayer-hyperlane-agent-relayer-0 9090 -n mainnet3 &

Wait a few seconds for the port-forward to establish.

Step 3: Get Domain IDs for Chains

Look up domain IDs from the registry:

cat node_modules/.pnpm/@hyperlane-xyz+registry@*/node_modules/@hyperlane-xyz/registry/dist/chains/<chain>/metadata.json | jq '.domainId'

Common domain IDs:

• ethereum: 1
• optimism: 10
• arbitrum: 42161
• polygon: 137
• base: 8453
• unichain: 130
• avalanche: 43114

Step 4: Query Relayer API

For each destination chain, query the relayer API:

curl -s 'http://localhost:9090/list_operations?destination_domain=<DOMAIN_ID>' > /tmp/<chain>.json

The response contains operations with:

• id

  : Message ID (H256)

• operation.message.sender

  : Sender address

• operation.message.recipient

  : Recipient address

• operation.num_retries

  : Number of retries (higher = more stuck)

• operation.status

  : Error status (e.g.,

  {"Retry": "ErrorEstimatingGas"}

  )

• operation.message.origin

  : Origin domain ID

• operation.message.destination

  : Destination domain ID

• operation.app_context

  : App context name

Step 5: Filter Messages by App Context

Look up the

app_context

rust/main/app-contexts/mainnet_config.json

jq '.metricAppContexts[] | select(.name == "<APP_CONTEXT>")' rust/main/app-contexts/mainnet_config.json

Filter API results to only include messages where:

• operation.message.recipient

  matches one of the

  recipientAddress

  values for that destination domain

Important: Addresses are padded to 32 bytes (H256 format).

Step 6: Query GCP Logs for Actual Errors

Calculate log freshness based on retry count:

The relayer uses exponential backoff (see

calculate_msg_backoff

rust/main/agents/relayer/src/msg/pending_message.rs

--freshness=1h

--freshness=3h

--freshness=12h

--freshness=24h

--freshness=3d

--freshness=7d

For each message ID, query GCP logs with calculated freshness:

gcloud logging read 'resource.type=k8s_container AND resource.labels.namespace_name=mainnet3 AND resource.labels.pod_name:omniscient-relayer AND jsonPayload.span.id:<MESSAGE_ID> AND jsonPayload.fields.error:*' --project=abacus-labs-dev --limit=1 --format='value(jsonPayload.fields.error)' --freshness=<CALCULATED_FRESHNESS>

Extract the human-readable error from the response using

sed

echo "$raw_error" | sed -n 's/.*execution reverted: \([^"]*\)".*/\1/p' | head -1

Common error patterns:

• "execution reverted: Nonce already used"

  → "Nonce already used"

• "execution reverted: panic: arithmetic underflow"

  → "Arithmetic underflow"

Note: Do not use

grep -P

Step 7: Present Investigation Results

Output a detailed summary table with full message IDs and both error sources:

## Investigation Results for [APP_CONTEXT]

### Summary
- Total stuck messages: X
- Destinations affected: [list]
- Reprepare reasons: ErrorEstimatingGas (N), CouldNotFetchMetadata (M)

### Messages

| Message ID | Retries | Reprepare Reason | Error | Origin |
|------------|---------|------------------|-----------|--------|
| `0xaa18ebc1c79345e6d24984a0b9a5ab66c968d128d46b2357b641e56e71b8d30c` | 47 | ErrorEstimatingGas | Nonce already used | optimism |
| `0xd6aeef7c092a88aa23ad53227aeb834ae731d059b3ce749db8451e761f3f15ac` | 47 | ErrorEstimatingGas | Nonce already used | arbitrum |

**Important**: Always show the full 66-character message ID (0x + 64 hex chars). Do not truncate.

### Error Analysis
[Explain based on the actual log errors found]

### Next Steps
To denylist these messages, run:
/denylist-stuck-messages <message_ids> app_context=APP_CONTEXT

Column definitions:

• Reprepare Reason: From

  operation.status

  in relayer API (e.g., ErrorEstimatingGas, CouldNotFetchMetadata)
• Error: Actual revert reason from GCP logs (e.g., "Nonce already used", "Arithmetic underflow")

Step 8: Output Denylist Command

At the end of the investigation results, output the full denylist command:

### Next Steps
To denylist, run:
/denylist-stuck-messages 0xaa18ebc1c79345e6d24984a0b9a5ab66c968d128d46b2357b641e56e71b8d30c 0xd6aeef7c092a88aa23ad53227aeb834ae731d059b3ce749db8451e761f3f15ac app_context=APP_CONTEXT

Always use full message IDs, never truncated.

Error Status Reference

ErrorEstimatingGas

CouldNotFetchMetadata

ApplicationReport(...)

GasPaymentNotFound

Error Handling

• Port-forward fails: Check kubectl context:

  kubectl config current-context

• No messages found: Queue may have cleared; alert may be stale
• API returns error: Check relayer pod:

  kubectl get pods -n mainnet3 | grep relayer

• App context not found: May be new/custom; ask user for sender/recipient addresses

Prerequisites

• kubectl

  configured with access to mainnet cluster
• Grafana MCP server connected (for alert URL parsing)