OpenClaw Silent Message Loss / Replay: 2026 Delivery Reliability Troubleshooting Guide

openclawdelivery reliabilitysilent message lossreplaytroubleshooting

If you’ve seen any of these symptoms, this guide is for you:

This is not just a model-quality problem. It’s a delivery reliability problem.

Verified signals from the last 7 days

Bottom line: a successful LLM call does not guarantee successful user delivery.

1) 5-minute triage: expose failures first

Run baseline checks:

openclaw status
openclaw gateway status --deep
openclaw logs --follow

Watch for three classes of signals:

  1. Channel send failures (Telegram/Discord/plugin channels)
  2. Repeated retry/recovery patterns
  3. Duplicate delivery after stop/restart events

At minimum, add temporary alerting on log keywords:

2) Top 4 root causes (priority order)

Root cause 1: Channel failures are not surfaced clearly

Typical pattern: delivery fails at plugin/channel layer, but conversation looks “normal”.

Evidence: #29126, #29124

How to confirm:

Root cause 2: Recovery path conflicts with stop/abort semantics

Typical pattern: you stop a run, but recovery later re-delivers partial/old outputs.

Evidence: #29127

How to confirm:

Root cause 3: Crash-induced state mismatch

Typical pattern: gateway crashes mid-generation; queue/history state diverges.

Evidence: #29125

How to confirm:

Root cause 4: Platform-specific edge cases (especially Telegram groups/topics)

Typical pattern: specific chat modes drop messages more often.

Evidence: #29238

How to confirm:

3) Execution checklist

Step 1 — Build minimal lifecycle observability

You should be able to answer:

If your current stack cannot answer these, instrument logs first.

Step 2 — Run bucketed tests

Split tests into:

Run 20–50 short messages per bucket. Track success rate and latency.

Step 3 — Validate stop/abort behavior

Test /stop / abort / restart and look for replay. If replay exists, add app-level idempotency (dedupe IDs or replay guards).

Step 4 — Make failures visible

Critical baseline:

4) Stability recommendations for production

  1. Use one active polling instance per critical channel (especially Telegram)
  2. Track delivery-success SLI separately from model-success SLI
  3. Separate model-failure and delivery-failure alert routes
  4. Run a short channel regression suite before each upgrade

5) Who should prioritize this now

Highest priority:

If you only run single-user DM usage, risk is lower—but failure alerting is still worth adding.

Core Guides (Recommended)

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