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icecube-evolution冰块进化

Agent Skill

icecube-evolution 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:icecube-evolution(冰块进化)
来源仓库:https://github.com/ares521521-design/icecube-evolution
安装命令:
openclaw skills install icecube-evolution
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install icecube-evolution

简介

持续收集任务执行反馈,自动优化代理行为模式与能力边界。

  • 适用于长期运行 Agent 的自我迭代与错误修正需求。
  • 安装命令为 openclaw skills install icecube-evolution,后台静默运行。
  • 需开启日志记录功能以便追踪改进轨迹。
  • 进化过程无需人工干预,但重大变更建议保留快照。

SKILL.md

name
icecube-evolution
description
🧊 IceCube Evolution — 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] → Log to mistake_log.md → Generate improvement → Queue
[Success detected] → Log to success_patterns.md → Pattern captured → Ready for reuse
[Heartbeat triggers] → Process queue → Apply improvements → Verify → 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 → AGENTS.md / SOUL.md
  • Workflow change → procedural memory
  • Tool addition → skill install
  • Config change → openclaw.json

From successes:

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

Improvement Types

TypeDestinationExample
rule_updateAGENTS.md"Always check X before Y"
workflow_changeprocedural/New step in launch process
tool_additionClawHubInstall new skill
config_changeopenclaw.jsonAdjust reserveTokensFloor
pattern_promotionMEMORY.mdSuccess pattern becomes durable rule
persona_updateSOUL.mdTone adjustment based on feedback

Verification Loop

Every improvement must verify:

  1. Apply — Make the change
  2. Test — Run relevant task
  3. Verify — Confirm improvement worked
  4. Close — 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

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 → logged
  • Memory retrieval success → 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 — Use freely.


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

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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