openclaw - 💡(How to fix) Fix [Feature]: Distinguish user input from AI model output in conversation history

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OpenClaw currently lacks a reliable mechanism to distinguish whether a message in the conversation history originated from user input or from AI model output, making it difficult for skills, hooks, and custom integrations to properly trace message provenance.

Root Cause

OpenClaw currently lacks a reliable mechanism to distinguish whether a message in the conversation history originated from user input or from AI model output, making it difficult for skills, hooks, and custom integrations to properly trace message provenance.

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Summary

OpenClaw currently lacks a reliable mechanism to distinguish whether a message in the conversation history originated from user input or from AI model output, making it difficult for skills, hooks, and custom integrations to properly trace message provenance.

Problem to solve

When building skills or debugging conversation flows, developers need to know the origin of each message. Currently, the internal message/context structure does not consistently carry role annotations or source metadata to distinguish user input from AI model output or tool call results.

Proposed solution

Add explicit role/source metadata to each message in the conversation context, e.g. role: "user" | "assistant" | "tool". This metadata should be accessible both at runtime (via context API) and in persisted conversation records for reliable message provenance tracing.

Impact

  • Affected: Skill developers, conversation debugging
  • Severity: Medium - ambiguity in message interpretation
  • Frequency: Always - every multi-turn conversation
  • Consequence: Harder to build reliable skills; debugging more difficult without clear message attribution.

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openclaw - 💡(How to fix) Fix [Feature]: Distinguish user input from AI model output in conversation history