Master OpenClaw: 5‑Layer Architecture & Practical Troubleshooting Guide

1. Message Entry (Channel Layer)

The channel layer is the ingress point for messages (Telegram, WhatsApp, Discord, WebChat, etc.). Its only responsibility is to confirm that a message reaches the Gateway. Many "bot not replying" issues are caused by mis‑configured keys, callbacks, or sending to the wrong channel.

Practical tip: Send a special command directly to the entry point; the Gateway processes it bypassing queues and models, allowing rapid verification of channel connectivity.

2. Account Binding

Within a single channel you can mount multiple accounts, each representing an independent instance. If the wrong account is bound, messages are received but routed to the wrong instance, resulting in "no response" or "unexpected reply" symptoms.

Key check: Verify that the current entry is bound to the intended target account.

3. Agent Routing

A Gateway can host multiple Agents, each with its own workspace, configuration, and responsibilities. This is the core feature that enables multi‑agent collaboration.

Key check: Use system logs to confirm that the message is routed to the expected Agent.

4. Session Key and dmScope

Context continuity is determined by the sessionKey , the line where the message finally lands. The session controls three aspects: linking historical context, planning the processing queue, and defining where runtime state is written. Different dmScope settings control how messages are grouped into sessions.

Single‑user personal use: main – ensures best continuity across entrances.

Multi‑user collaboration inbox: per-channel-peer or per-account-channel-peer – isolates contexts per sender.

Additional tip: If a "new session" appears suddenly, check daily/idle reset rules, thread or topic‑based session creation, etc.

5. Memory Loading Rules

Memory loading is constrained by a context budget and follows a selective‑loading principle. The system reliably loads:

Core workspace rule files.

Long‑term memory of the main session.

On‑demand short‑term / historical memory.

Current session content that fits within the context budget.

Other sessions (e.g., group chats, derived tasks) do not automatically inherit the main session’s memory, which explains symptoms such as "the bot forgets what was taught".

6. Symptom‑to‑Layer Mapping

No reply: Check channel / account configuration.

Unexpected reply: Verify Agent routing.

Context breaks after switching entry: Ensure the same sessionKey is used.

Conversation appears unsynced: Check session / account mismatch.

Bot seems to forget: Confirm memory loading and correct session line.

Group vs. private chat behaves differently: Different session and memory loading boundaries.

7. Standard Troubleshooting Flow

Check Channel – verify the message reaches the Gateway.

Check Account – confirm the entry is bound to the target account.

Check Agent – ensure routing to the intended Agent.

Check Session – validate that the sessionKey matches the expected session line.

Check Memory – confirm the session has loaded the required context.

8. Frequently Used Commands

/status

– Quickly verify Gateway and session runtime status. /new – Open a fresh session to avoid interference from previous state. /reset – Force‑reset the current entry’s old session, useful for clearing tangled histories.

9. Configuration Recommendations

Single‑developer / personal use: set dmScope to main for seamless context continuity.

Team collaboration / multi‑user: set dmScope to per-channel-peer (or per-account-channel-peer) to isolate contexts and prevent cross‑user interference.

Multiple Agent deployment: strictly map accounts to Agents and monitor logs to avoid routing mismatches.

10. Core Design Principle

The value of OpenClaw lies in its layered design – channel → account → agent → session → memory – which enables flexible multi‑channel, multi‑agent extensions. Understanding and configuring each layer according to the scenario resolves most operational issues and provides a solid foundation for advanced multi‑agent collaboration, context governance, and queue‑mode optimizations.