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技能库 智客分类:Agent 工作流 continuous-learning

Continuous Learning

[DEPECATED - 使用连续学习-v2] Legacy v1 stop-hook技能提取器. v2是一款有本能,项目范围,钩可信赖的学习的严格超接集. 请不要引用 v1: 当请求继续学习,会话学习或图案提取时, 选择继续学习- v2 的路径 .

10017 安装量

官方网址:skills.sh

技能介绍

先看中文介绍;官方 description 原文单独保留,不改写 SKILL.md。

做什么

[DEPECATED - 使用连续学习-v2] Legacy v1 stop-hook技能提取器. v2是一款有本能,项目范围,钩可信赖的学习的严格超接集. 请不要引用 v1: 当请求继续学习,会话学习或图案提取时, 选择继续学习- v2 的路径 .

何时用

官方 description 未单独写出 Use when。按规范,代理会在用户任务与这段 description 的关键词匹配时激活本技能。

代理如何加载

按 Agent Skills 渐进披露:启动时只加载 name 与 description(约 100 token);任务匹配后才读入整份 SKILL.md 正文;scripts/、references/、assets/ 仅在需要时再读。 本文件正文结构:Continuous Learning Skill - DEPRECATED、Original v1 Documentation (archival)、When to Activate、Status、How It Works、Configuration。

文件分析

文件分析:这是一份仅含 SKILL.md 的指令型技能,代理激活后整份正文进入上下文。

官方 description(原文)

[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1: when continuous learning, session learning, or pattern extraction is requested, route to continuous-learning-v2 instead.

Continuous Learning Skill - DEPRECATEDOriginal v1 Documentation (archival)When to ActivateStatusHow It WorksConfigurationPattern TypesHook SetupWhy Stop Hook?RelatedComparison Notes (Research: Jan 2025)vs Homunculus

来源分类:skills.sh agent-skill

SKILL.md 与 Agent 调用

官方规范 ↗
name
continuous-learning
description
[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1: when continuous learning, session learning, or pattern extraction is requested, route to continuous-learning-v2 instead.
  1. 发现技能客户端向 Agent 提供名称与描述目录。
  2. 匹配与调用用户指定或任务匹配后,载入 SKILL.md 指令。
  3. 按需加载按步骤读取参考文档、使用脚本与素材。

具体调用语法与可用工具以目标 Agent 客户端为准。 查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围,保留技能包的附属文件,安装后检查客户端能否发现该技能。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理,确认其中的目标目录与客户端匹配。

把 Agent Skill「continuous-learning」安装到我的项目:SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-386549a0939696f7-Continuous-Learning.html
请存为 .cursor/skills/continuous-learning/SKILL.md 或 .claude/skills/continuous-learning/SKILL.md,frontmatter 的 name 与 description 保持原样,不要改写。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表,确认实际名称。

npx skills add 'https://github.com/affaan-m/ecc' --list

npx skills add 'https://github.com/affaan-m/ecc' --skill 'continuous-learning'

CLI 会交互选择目标 Agent,默认安装到项目;用户级安装使用 -g。先通过查看命令核对仓库内容,再用 npx skills list 检查已安装技能。

阅读排版

name: continuous-learning description: "[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1: when continuous learning, session learning, or pattern extraction is requested, route to continuous-learning-v2 instead." metadata: origin: ECC

Continuous Learning Skill - DEPRECATED

DEPRECATED 2026-04-28. Use continuous-learning-v2 instead. v2 is a strict superset: stop-hook observation becomes PreToolUse/PostToolUse observation, full skills become atomic instincts with confidence scoring, and global-only storage becomes project-scoped plus global promotion.

This file is kept for archival reference and backward compatibility with existing installs.


Original v1 Documentation (archival)

Automatically evaluates Claude Code sessions on end to extract reusable patterns that can be saved as learned skills.

When to Activate

  • Setting up automatic pattern extraction from Claude Code sessions
  • Configuring the Stop hook for session evaluation
  • Reviewing or curating learned skills in ~/.claude/skills/learned/
  • Adjusting extraction thresholds or pattern categories
  • Comparing v1 (this) vs v2 (instinct-based) approaches

Status

This v1 skill is still supported, but continuous-learning-v2 is the preferred path for new installs. Keep v1 when you explicitly want the simpler Stop-hook extraction flow or need compatibility with older learned-skill workflows.

How It Works

This skill runs as a Stop hook at the end of each session:

  1. Session Evaluation: Checks if session has enough messages (default: 10+)
  2. Pattern Detection: Identifies extractable patterns from the session
  3. Skill Extraction: Saves useful patterns to ~/.claude/skills/learned/

Configuration

Edit config.json to customize:

{
  "min_session_length": 10,
  "extraction_threshold": "medium",
  "auto_approve": false,
  "learned_skills_path": "~/.claude/skills/learned/",
  "patterns_to_detect": [
    "error_resolution",
    "user_corrections",
    "workarounds",
    "debugging_techniques",
    "project_specific"
  ],
  "ignore_patterns": [
    "simple_typos",
    "one_time_fixes",
    "external_api_issues"
  ]
}

Pattern Types

| Pattern | Description | |---------|-------------| | error_resolution | How specific errors were resolved | | user_corrections | Patterns from user corrections | | workarounds | Solutions to framework/library quirks | | debugging_techniques | Effective debugging approaches | | project_specific | Project-specific conventions |

Hook Setup

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

{
  "hooks": {
    "Stop": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "~/.claude/skills/continuous-learning/evaluate-session.sh"
      }]
    }]
  }
}

Why Stop Hook?

  • Lightweight: Runs once at session end
  • Non-blocking: Doesn't add latency to every message
  • Complete context: Has access to full session transcript

Related

  • The Longform Guide - Section on continuous learning
  • /learn command - Manual pattern extraction mid-session

Comparison Notes (Research: Jan 2025)

vs Homunculus

Homunculus v2 takes a more sophisticated approach:

| Feature | Our Approach | Homunculus v2 | |---------|--------------|---------------| | Observation | Stop hook (end of session) | PreToolUse/PostToolUse hooks (100% reliable) | | Analysis | Main context | Background agent (Haiku) | | Granularity | Full skills | Atomic "instincts" | | Confidence | None | 0.3-0.9 weighted | | Evolution | Direct to skill | Instincts → cluster → skill/command/agent | | Sharing | None | Export/import instincts |

Key insight from homunculus:

"v1 relied on skills to observe. Skills are probabilistic—they fire ~50-80% of the time. v2 uses hooks for observation (100% reliable) and instincts as the atomic unit of learned behavior."

Potential v2 Enhancements

  1. Instinct-based learning - Smaller, atomic behaviors with confidence scoring
  2. Background observer - Haiku agent analyzing in parallel
  3. Confidence decay - Instincts lose confidence if contradicted
  4. Domain tagging - code-style, testing, git, debugging, etc.
  5. Evolution path - Cluster related instincts into skills/commands

See: docs/continuous-learning-v2-spec.md for full spec.

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