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Agent Skill · 开发

lobster-continuous-learning-v2(龙虾持续学习 v2)

lobster-continuous-learning-v2 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。

lobster-continuous-learning-v2 是开发类 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,按安装量在开发类的 21,746 个 Skill 里排第 10,312。

总安装 2,304周安装 96GitHub Stars 公开资料未说明下载 768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:lobster-continuous-learning-v2(龙虾持续学习 v2)
来源仓库:https://github.com/wangxiaofei860208-source/lobster-continuous-learning-v2
安装命令:
openclaw skills install lobster-continuous-learning-v2
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 lobster-continuous-learning-v2

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

lobster-continuous-learning-v2 基于本能观察会话,创建原子本能并演化为技能,适合 OpenClaw 中持续学习能力构建。适用于从交互中自动提取经验,形成可复用命令或代理行为。通过置信度评分筛选有效学习内容,支持长期能力进化。需监控学习过程的数据质量,防止错误模式固化。

建议定期清理低置信度记录以确保系统可靠性。

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 lobster-continuous-learning-v2;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

lobster-continuous-learning-v2 怎么安装?

在终端执行 openclaw skills install lobster-continuous-learning-v2。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

lobster-continuous-learning-v2 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。

lobster-continuous-learning-v2 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。

lobster-continuous-learning-v2 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。

lobster-continuous-learning-v2 用的人多吗?

公开数据是累计安装 2,304 次,近一周安装 96 次,下载 768 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。

lobster-continuous-learning-v2 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。
  • 需要处理开发类任务、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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
lobster-continuous-learning-v2

龙虾持续学习 v2 · 本页

2,304—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
lobster-continuous-learning-v2
description
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
origin
ECC
version
2.1.0

Continuous Learning v2.1 - Instinct

-Based Architecture

An advanced learning system that turns your Claude Code sessions into reusable knowledge through atomic "instincts" - small learned behaviors with confidence scoring.

v2.1 adds project-scoped instincts — React patterns stay in your React project, Python conventions stay in your Python project, and universal patterns (like "always validate input") are shared globally.

When to Activate

  • Setting up automatic learning from Claude Code sessions
  • Configuring instinct-based behavior extraction via hooks
  • Tuning confidence thresholds for learned behaviors
  • Reviewing, exporting, or importing instinct libraries
  • Evolving instincts into full skills, commands, or agents
  • Managing project-scoped vs global instincts
  • Promoting instincts from project to global scope

What's New in v2.1

Featurev2.0v2.1
StorageGlobal (~/.claude/homunculus/)Project-scoped (projects/<hash>/)
ScopeAll instincts apply everywhereProject-scoped + global
DetectionNonegit remote URL / repo path
PromotionN/AProject → global when seen in 2+ projects
Commands4 (status/evolve/export/import)6 (+promote/projects)
Cross-projectContamination riskIsolated by default

What's New in v2 (vs v1)

Featurev1v2
ObservationStop hook (session end)PreToolUse/PostToolUse (100% reliable)
AnalysisMain contextBackground agent (Haiku)
GranularityFull skillsAtomic "instincts"
ConfidenceNone0.3-0.9 weighted
EvolutionDirect to skillInstincts -> cluster -> skill/command/agent
SharingNoneExport/import instincts

The Instinct Model

An instinct is a small learned behavior:

---
id: prefer-functional-style
trigger: "when writing new functions"
confidence: 0.7
domain: "code-style"
source: "session-observation"
scope: project
project_id: "a1b2c3d4e5f6"
project_name: "my-react-app"
---

# Prefer Functional Style

## Action
Use functional patterns over classes when appropriate.

## Evidence
- Observed 5 instances of functional pattern preference
- User corrected class-based approach to functional on 2025-01-15

Properties:

  • Atomic -- one trigger, one action
  • Confidence-weighted -- 0.3 = tentative, 0.9 = near certain
  • Domain-tagged -- code-style, testing, git, debugging, workflow, etc.
  • Evidence-backed -- tracks what observations created it
  • Scope-aware -- project (default) or global

How It Works

Session Activity (in a git repo)
      |
      | Hooks capture prompts + tool use (100% reliable)
      | + detect project context (git remote / repo path)
      v
+---------------------------------------------+
|  projects/<project-hash>/observations.jsonl  |
|   (prompts, tool calls, outcomes, project)   |
+---------------------------------------------+
      |
      | Observer agent reads (background, Haiku)
      v
+---------------------------------------------+
|          PATTERN DETECTION                   |
|   * User corrections -> instinct             |
|   * Error resolutions -> instinct            |
|   * Repeated workflows -> instinct           |
|   * Scope decision: project or global?       |
+---------------------------------------------+
      |
      | Creates/updates
      v
+---------------------------------------------+
|  projects/<project-hash>/instincts/personal/ |
|   * prefer-functional.yaml (0.7) [project]   |
|   * use-react-hooks.yaml (0.9) [project]     |
+---------------------------------------------+
|  instincts/personal/  (GLOBAL)               |
|   * always-validate-input.yaml (0.85) [global]|
|   * grep-before-edit.yaml (0.6) [global]     |
+---------------------------------------------+
      |
      | /evolve clusters + /promote
      v
+---------------------------------------------+
|  projects/<hash>/evolved/ (project-scoped)   |
|  evolved/ (global)                           |
|   * commands/new-feature.md                  |
|   * skills/testing-workflow.md               |
|   * agents/refactor-specialist.md            |
+---------------------------------------------+

Project Detection

The system automatically detects your current project:

  1. CLAUDE_PROJECT_DIR env var (highest priority)
  2. git remote get-url origin -- hashed to create a portable project ID (same repo on different machines gets the same ID)
  3. git rev-parse --show-toplevel -- fallback using repo path (machine-specific)
  4. Global fallback -- if no project is detected, instincts go to global scope

Each project gets a 12-character hash ID (e.g., a1b2c3d4e5f6). A registry file at ~/.claude/homunculus/projects.json maps IDs to human-readable names.

Quick Start

1. Enable Observation Hooks

Add to your ~/.claude/settings.json.

If installed as a plugin (recommended):

{
  "hooks": {
    "PreToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "${CLAUDE_PLUGIN_ROOT}/skills/continuous-learning-v2/hooks/observe.sh"
      }]
    }],
    "PostToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "${CLAUDE_PLUGIN_ROOT}/skills/continuous-learning-v2/hooks/observe.sh"
      }]
    }]
  }
}

If installed manually to ~/.claude/skills:

{
  "hooks": {
    "PreToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh"
      }]
    }],
    "PostToolUse": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "~/.claude/skills/continuous-learning-v2/hooks/observe.sh"
      }]
    }]
  }
}

2. Initialize Directory Structure

The system creates directories automatically on first use, but you can also create them manually:

# Global directories
mkdir -p ~/.claude/homunculus/{instincts/{personal,inherited},evolved/{agents,skills,commands},projects}

# Project directories are auto-created when the hook first runs in a git repo

3. Use the Instinct Commands

/instinct-status     # Show learned instincts (project + global)
/evolve              # Cluster related instincts into skills/commands
/instinct-export     # Export instincts to file
/instinct-import     # Import instincts from others
/promote             # Promote project instincts to global scope
/projects            # List all known projects and their instinct counts

Commands

CommandDescription
/instinct-statusShow all instincts (project-scoped + global) with confidence
/evolveCluster related instincts into skills/commands, suggest promotions
/instinct-exportExport instincts (filterable by scope/domain)
/instinct-import <file>Import instincts with scope control
/promote [id]Promote project instincts to global scope
/projectsList all known projects and their instinct counts

Configuration

Edit config.json to control the background observer:

{
  "version": "2.1",
  "observer": {
    "enabled": false,
    "run_interval_minutes": 5,
    "min_observations_to_analyze": 20
  }
}
KeyDefaultDescription
observer.enabledfalseEnable the background observer agent
observer.run_interval_minutes5How often the observer analyzes observations
observer.min_observations_to_analyze20Minimum observations before analysis runs

Other behavior (observation capture, instinct thresholds, project scoping, promotion criteria) is configured via code defaults in instinct-cli.py and observe.sh.

File Structure

~/.claude/homunculus/
+-- identity.json           # Your profile, technical level
+-- projects.json           # Registry: project hash -> name/path/remote
+-- observations.jsonl      # Global observations (fallback)
+-- instincts/
|   +-- personal/           # Global auto-learned instincts
|   +-- inherited/          # Global imported instincts
+-- evolved/
|   +-- agents/             # Global generated agents
|   +-- skills/             # Global generated skills
|   +-- commands/           # Global generated commands
+-- projects/
    +-- a1b2c3d4e5f6/       # Project hash (from git remote URL)
    |   +-- project.json    # Per-project metadata mirror (id/name/root/remote)
    |   +-- observations.jsonl
    |   +-- observations.archive/
    |   +-- instincts/
    |   |   +-- personal/   # Project-specific auto-learned
    |   |   +-- inherited/  # Project-specific imported
    |   +-- evolved/
    |       +-- skills/
    |       +-- commands/
    |       +-- agents/
    +-- f6e5d4c3b2a1/       # Another project
        +-- ...

Scope Decision Guide

Pattern TypeScopeExamples
Language/framework conventionsproject"Use React hooks", "Follow Django REST patterns"
File structure preferencesproject"Tests in __tests__/", "Components in src/components/"
Code styleproject"Use functional style", "Prefer dataclasses"
Error handling strategiesproject"Use Result type for errors"
Security practicesglobal"Validate user input", "Sanitize SQL"
General best practicesglobal"Write tests first", "Always handle errors"
Tool workflow preferencesglobal"Grep before Edit", "Read before Write"
Git practicesglobal"Conventional commits", "Small focused commits"

Instinct Promotion (Project -> Global)

When the same instinct appears in multiple projects with high confidence, it's a candidate for promotion to global scope.

Auto-promotion criteria:

  • Same instinct ID in 2+ projects
  • Average confidence >= 0.8

How to promote:

# Promote a specific instinct
python3 instinct-cli.py promote prefer-explicit-errors

# Auto-promote all qualifying instincts
python3 instinct-cli.py promote

# Preview without changes
python3 instinct-cli.py promote --dry-run

The /evolve command also suggests promotion candidates.

Confidence Scoring

Confidence evolves over time:

ScoreMeaningBehavior
0.3TentativeSuggested but not enforced
0.5ModerateApplied when relevant
0.7StrongAuto-approved for application
0.9Near-certainCore behavior

Confidence increases when:

  • Pattern is repeatedly observed
  • User doesn't correct the suggested behavior
  • Similar instincts from other sources agree

Confidence decreases when:

  • User explicitly corrects the behavior
  • Pattern isn't observed for extended periods
  • Contradicting evidence appears

Why Hooks vs Skills for Observation?

"v1 relied on skills to observe. Skills are probabilistic -- they fire ~50-80% of the time based on Claude's judgment."

Hooks fire 100% of the time, deterministically. This means:

  • Every tool call is observed
  • No patterns are missed
  • Learning is comprehensive

Backward Compatibility

v2.1 is fully compatible with v2.0 and v1:

  • Existing global instincts in ~/.claude/homunculus/instincts/ still work as global instincts
  • Existing ~/.claude/skills/learned/ skills from v1 still work
  • Stop hook still runs (but now also feeds into v2)
  • Gradual migration: run both in parallel

Privacy

  • Observations stay local on your machine
  • Project-scoped instincts are isolated per project
  • Only instincts (patterns) can be exported — not raw observations
  • No actual code or conversation content is shared
  • You control what gets exported and promoted

Related

  • ECC-Tools GitHub App - Generate instincts from repo history
  • Homunculus - Community project that inspired the v2 instinct-based architecture (atomic observations, confidence scoring, instinct evolution pipeline)
  • The Longform Guide - Continuous learning section

*Instinct-based learning: teaching Claude your patterns, one project at a time.*

平台分布

OpenClaw

85.5%
按下载量换算657

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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