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BytesAgain β€Ί Skills β€Ί IceCube Evolution
πŸ¦€ ClawHub

IceCube Evolution

by @ares521521-design

🧊 IceCube Evolution β€” Continuous self-improvement system for AI agents. Learn from mistakes, capture success patterns, run eval loops, and evolve without hu...

Versionv1.0.0
Downloads311
#clawhub
TERMINAL
clawhub install icecube-evolution

πŸ“– About This Skill

name: icecube-evolution description: "🧊 IceCube Evolution β€” Continuous self-improvement system for AI agents. Learn from mistakes, capture success patterns, run eval loops, and evolve without human intervention. The engine that makes your agent smarter every day." metadata: openclaw: requires: {}

🧊 IceCube Evolution

The self-improvement engine for AI agents.

Not "learn when asked." Not "improve when bugs happen." Just constant, automatic evolution.

Why IceCube Evolution?

The problem:

  • Agents make the same mistakes repeatedly
  • Good patterns aren't captured
  • No systematic improvement
  • Improvement requires human intervention

    • The solution:

  • Log every mistake automatically
  • Capture every success pattern
  • Run improvement loops on schedule
  • Evolve without waiting for bugs

    • The result:

  • Mistakes decrease over time
  • Success patterns compound
  • Agent gets better daily
  • Zero manual intervention needed

    • Architecture

    Three Files, One Loop

    mistake_log.md: 

    # Mistake Log
    ML-2026-03-17-001
    

  • Date: 2026-03-17 14:32
    • 

  • Context: Task dispatch
    • 

  • Mistake: Did not check unclosed_work.yaml before starting new task
    • 

  • Impact: Created duplicate task, wasted resources
    • 

  • Fix: Add mandatory unclosed_work check to startup sequence
    • 

  • Status: fixed
    •

    success_patterns.md: 

    # Success Patterns
    SP-2026-03-17-001
    

  • Date: 2026-03-17 15:45
    • 

  • Context: Memory retrieval
    • 

  • Pattern: Run memory_search before acting on any past-context task
    • 

  • Result: Correct context loaded, no guessing
    • 

  • Applicability: Any task referencing previous work
    •

    improvement_queue.md: 

    # Improvement Queue
    IQ-2026-03-17-001
    

  • Type: rule_update
    • 

  • Source: ML-2026-03-17-001
    • 

  • Action: Add unclosed_work check to AGENTS.md startup
    • 

  • Priority: high
    • 

  • Status: pending
    •

    The Evolution Loop

    [Mistake detected] β†’ Log to mistake_log.md β†’ Generate improvement β†’ Queue
[Success detected] β†’ Log to success_patterns.md β†’ Pattern captured β†’ Ready for reuse
[Heartbeat triggers] β†’ Process queue β†’ Apply improvements β†’ Verify β†’ Close loop

    Setup

    1. Create Evolution Files

    mkdir -p ~/.openclaw/workspace/memory/system
touch ~/.openclaw/workspace/memory/system/mistake_log.md
touch ~/.openclaw/workspace/memory/system/success_patterns.md
touch ~/.openclaw/workspace/memory/system/improvement_queue.md
touch ~/.openclaw/workspace/memory/system/evolution_log.md

    2. Add to AGENTS.md

    ## Evolution Protocol
    Mistake Logging (Immediate)
    
When you make a recoverable error:
1. Log to mistake_log.md immediately
2. Do not wait for human to notice
3. Include: context, mistake, impact, fix
    Success Capture (Immediate)
    
When something works better than expected:
1. Log to success_patterns.md
2. Include: context, pattern, result, applicability
    Improvement Processing (Weekly via Heartbeat)
    
1. Scan mistake_log for unfixed entries
2. Scan success_patterns for unapplied patterns
3. Generate concrete improvement actions
4. Apply and verify

    3. Configure Heartbeat Integration

    ## Evolution Checks (Heartbeat)
    Daily
    

  • [ ] Scan mistake_log for new unfixed entries
    • 

  • [ ] Scan success_patterns for new patterns
    • 

  • [ ] Update evolution_log.md
    • Weekly
    

  • [ ] Process improvement_queue
    • 

  • [ ] Apply accumulated improvements
    • 

  • [ ] Verify fixes work
    • 

  • [ ] Generate evolution summary
    •

    Trigger Conditions

    Automatic Mistake Logging

  • Repeated fallback: Same fallback triggered 3+ times
  • Repeated rollback: Same rollback pattern 2+ times
  • User correction: User corrects same thing 2+ times
  • Task failure: Task marked failed without resolution
  • Context loss: Important info lost due to compaction

    • Automatic Success Capture

  • First-time success: Complex task completed without issues
  • Efficiency gain: Task done faster than previous similar task
  • User praise: User explicitly says "good" or "thanks"
  • Zero-error cycle: Multi-step process with no errors
  • Novel solution: Creative approach that worked

    • Improvement Generation

    From mistakes:

  • Rule update β†’ AGENTS.md / SOUL.md
  • Workflow change β†’ procedural memory
  • Tool addition β†’ skill install
  • Config change β†’ openclaw.json

    • From successes:

  • Pattern promotion β†’ MEMORY.md
  • Procedure capture β†’ memory/procedural/
  • Tool recommendation β†’ TOOLS.md
  • Best practice β†’ skill SKILL.md

    • Improvement Types

    | Type | Destination | Example | |------|-------------|---------| | rule_update | AGENTS.md | "Always check X before Y" | | workflow_change | procedural/ | New step in launch process | | tool_addition | ClawHub | Install new skill | | config_change | openclaw.json | Adjust reserveTokensFloor | | pattern_promotion | MEMORY.md | Success pattern becomes durable rule | | persona_update | SOUL.md | Tone adjustment based on feedback |

    Verification Loop

    Every improvement must verify:

    1. Apply β€” Make the change 2. Test β€” Run relevant task 3. Verify β€” Confirm improvement worked 4. Close β€” Mark as fixed/applied in queue

    If verification fails:

  • Log new mistake
  • Rollback if needed
  • Queue alternative improvement

    • Metrics

    Track in evolution_log.md:

    # Evolution Log
    Week 2026-03-17 to 2026-03-23
    

  • Mistakes logged: 5
    • 

  • Mistakes fixed: 4
    • 

  • Successes captured: 7
    • 

  • Improvements applied: 6
    • 

  • Improvements verified: 5
    • 

  • Pending improvements: 1
    • Trend
    

  • Mistake rate: decreasing (-20% vs last week)
    • 

  • Success rate: increasing (+15% vs last week)
    • 

  • Improvement velocity: stable
    • Top Improvements This Week
    
1. Added unclosed_work check (reduced duplicate tasks)
2. Captured memory_search pattern (reduced guessing)
3. Installed xiaohongshu skill (enabled new capability)

    Anti-Patterns

    ❌ Don't:

  • Wait for user to notice mistakes
  • Log mistakes without fixes
  • Apply improvements without verification
  • Let improvement queue grow unbounded
  • Skip evolution during busy periods

    • βœ… Do:

  • Log immediately when mistake happens
  • Every mistake has a concrete fix
  • Every improvement has verification steps
  • Process queue weekly, don't accumulate
  • Evolution never stops, only pauses for urgent tasks

    • Integration with IceCube Suite

    icecube-memory: Evolution logs stored in memory structure icecube-heartbeat: Heartbeat triggers evolution processing icecube-ops: Ops improvements feed into evolution queue

    Example Evolution Cycle

    Monday:

  • Task dispatch mistake β†’ logged
  • Memory retrieval success β†’ captured
  • 2 improvements queued

    • Wednesday (Heartbeat):

  • Process queue
  • Apply rule update to AGENTS.md
  • Apply pattern to MEMORY.md
  • Verify both work

    • Friday:

  • Weekly evolution summary
  • Metrics show mistake rate down
  • Success rate up
  • 2 new improvements pending

    • License

    MIT β€” Use freely.

    *Mistakes are fuel. Successes are patterns. Evolution is the engine.*

    βš™οΈ Configuration

    1. Create Evolution Files

    mkdir -p ~/.openclaw/workspace/memory/system
touch ~/.openclaw/workspace/memory/system/mistake_log.md
touch ~/.openclaw/workspace/memory/system/success_patterns.md
touch ~/.openclaw/workspace/memory/system/improvement_queue.md
touch ~/.openclaw/workspace/memory/system/evolution_log.md

    2. Add to AGENTS.md

    ```markdown