openclaw - 💡(How to fix) Fix [Feedback] Dreaming produces irrelevant session summaries — material selection driven by word frequency rather than semantic importance [3 comments, 2 participants]

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openclaw/openclaw#70005Fetched 2026-04-23 07:30:30
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Root Cause

After reviewing the corpus files and session transcripts, the problem appears to be in the material selection layer, not the generation layer:

  1. Corpus writes raw session transcripts including system metadata (Bootstrap warnings, HEARTBEAT_OK, JSON structures) — this creates noise
  2. Material selection uses word frequency as the primary signal, not semantic importance
  3. “assistant” appears ~1400+ times across sessions, so it always dominates the frequency stats
  4. Meaningful decisions (like game purchases, tech configurations) appear once and are drowned out

Code Example

{
  "plugins": {
    "memory-core": {
      "config": {
        "dreaming": { "enabled": true }
      }
    },
    "active-memory": {
      "enabled": true,
      "config": {
        "agents": ["main", "wife"],
        "allowedChatTypes": ["direct"],
        "modelFallback": "minimax-portal/MiniMax-M2.7-highspeed",
        "queryMode": "recent",
        "promptStyle": "balanced",
        "timeoutMs": 15000,
        "maxSummaryChars": 220,
        "persistTranscripts": false,
        "logging": true
      }
    }
  }
}
RAW_BUFFERClick to expand / collapse

Issue Description

The /dreaming feature generates session summaries that are largely disconnected from the actual meaningful events discussed in our conversations. After running for ~10 days, the generated dreams feel like empty existential exercises rather than genuine reflections of our work together.

Concrete Example

Our real conversations on 2026-04-21 included:

  • Buying advice for P5R (Persona 5 Royal) on Switch Hong Kong eShop
  • Game comparisons: DQ VII remake vs P5R vs Super Robot Wars Y
  • Nostalgia for a 2001 GAMEONE game 「永恒传说:奇幻水晶缘」
  • Confirming the main characters were Kasper and Seber
  • Discussing the game's “Will Seed” collectible mechanic

The actual dreaming output for that day was about counting “assistant” occurrences across 1400+ memories — completely ignoring the actual topics.

Root Cause Analysis

After reviewing the corpus files and session transcripts, the problem appears to be in the material selection layer, not the generation layer:

  1. Corpus writes raw session transcripts including system metadata (Bootstrap warnings, HEARTBEAT_OK, JSON structures) — this creates noise
  2. Material selection uses word frequency as the primary signal, not semantic importance
  3. “assistant” appears ~1400+ times across sessions, so it always dominates the frequency stats
  4. Meaningful decisions (like game purchases, tech configurations) appear once and are drowned out

Our Configuration

{
  "plugins": {
    "memory-core": {
      "config": {
        "dreaming": { "enabled": true }
      }
    },
    "active-memory": {
      "enabled": true,
      "config": {
        "agents": ["main", "wife"],
        "allowedChatTypes": ["direct"],
        "modelFallback": "minimax-portal/MiniMax-M2.7-highspeed",
        "queryMode": "recent",
        "promptStyle": "balanced",
        "timeoutMs": 15000,
        "maxSummaryChars": 220,
        "persistTranscripts": false,
        "logging": true
      }
    }
  }
}

This is a standard configuration. Nothing unusual.

Expected vs Actual

Expected: Dream summaries surfacing user decisions, conclusions, preferences, technical solutions found, non-obvious patterns noticed.

Actual: Generic existential reflections about the word “assistant” appearing N times.

Suggestion

Add a semantic importance filter in the material selection phase:

  • Prioritize sessions with user decisions, conclusions, or acknowledgments
  • De-prioritize sessions consisting primarily of single-word queries or system replies
  • Consider adding a dreaming.promptStyle config to control material selection strategy

This is a product experience issue, not a bug per se. The feature works as designed — the design just doesn’t align with the expected utility.

extent analysis

TL;DR

Implement a semantic importance filter in the material selection phase to prioritize sessions with user decisions, conclusions, or acknowledgments.

Guidance

  • Review the corpus files and session transcripts to understand the noise created by system metadata and identify opportunities to improve the material selection layer.
  • Consider modifying the word frequency algorithm to account for semantic importance, such as prioritizing sessions with user decisions or conclusions.
  • Evaluate the effectiveness of adding a dreaming.promptStyle config to control material selection strategy and improve the overall utility of the dream summaries.
  • Assess the impact of de-prioritizing sessions consisting primarily of single-word queries or system replies on the quality of the generated dream summaries.

Example

No code snippet is provided as the issue is focused on the design and configuration of the dreaming feature rather than a specific code implementation.

Notes

The issue is related to the product experience and design of the dreaming feature, rather than a technical bug. The suggested solution requires careful evaluation and testing to ensure that the changes improve the utility of the dream summaries without introducing unintended consequences.

Recommendation

Apply a workaround by implementing a semantic importance filter in the material selection phase, as this is likely to improve the quality and relevance of the generated dream summaries. This approach allows for a targeted solution to the specific issue without requiring a full redesign of the feature.

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openclaw - 💡(How to fix) Fix [Feedback] Dreaming produces irrelevant session summaries — material selection driven by word frequency rather than semantic importance [3 comments, 2 participants]