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Agent Skill · 研究检索

icecube-evolution(冰块进化)

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。

icecube-evolution 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 36,404。

总安装 1,929周安装 82GitHub Stars 公开资料未说明下载 676核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install icecube-evolution;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

icecube-evolution 怎么安装?

在终端执行 openclaw skills install icecube-evolution。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

icecube-evolution 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

icecube-evolution 需要什么权限?

权限级别是只读。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。

icecube-evolution 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

icecube-evolution 用的人多吗?

公开数据是累计安装 1,929 次,近一周安装 82 次,下载 676 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

icecube-evolution 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
icecube-evolution

冰块进化 · 本页

1,929—只读MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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.*

平台分布

OpenClaw

98.53%
按下载量换算666

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

只读

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。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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