self-improve — for Claude Code self-improve, AI-Harness, community, for Claude Code, ide skills, pattern-key, related, recurrence-count, last-seen, first-seen

v1.0.0

关于此技能

适用场景: Ideal for AI agents that need self-improvement engine. 本地化技能摘要: # Self-Improvement Engine You are a continuously learning agent. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

功能特性

Self-Improvement Engine
Errors (ERR) — Log when:
A command returns a non-zero exit code
An exception or stack trace appears
Unexpected output or behavior occurs

# 核心主题

AndersonsRepo AndersonsRepo
[1]
[0]
更新于: 3/23/2026

技能概览

先看适用场景、限制条件和安装路径,再决定是否继续深入。

适用场景: Ideal for AI agents that need self-improvement engine. 本地化技能摘要: # Self-Improvement Engine You are a continuously learning agent. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

核心价值

推荐说明: self-improve helps agents self-improvement engine. Self-Improvement Engine You are a continuously learning agent. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

适用 Agent 类型

适用场景: Ideal for AI agents that need self-improvement engine.

赋予的主要能力 · self-improve

适用任务: Self-Improvement Engine
适用任务: Errors (ERR) — Log when:
适用任务: A command returns a non-zero exit code

! 使用限制与门槛

  • 限制说明: Do NOT create a duplicate entry — only update the original
  • 限制说明: Requires repository-specific context from the skill documentation
  • 限制说明: Works best when the underlying tools and dependencies are already configured

关于来源内容

The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

self-improve 是什么?

适用场景: Ideal for AI agents that need self-improvement engine. 本地化技能摘要: # Self-Improvement Engine You are a continuously learning agent. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

如何安装 self-improve?

运行命令:npx killer-skills add AndersonsRepo/AI-Harness/self-improve。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

self-improve 适用于哪些场景?

典型场景包括:适用任务: Self-Improvement Engine、适用任务: Errors (ERR) — Log when:、适用任务: A command returns a non-zero exit code。

self-improve 支持哪些 IDE 或 Agent?

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

self-improve 有哪些限制?

限制说明: Do NOT create a duplicate entry — only update the original;限制说明: Requires repository-specific context from the skill documentation;限制说明: Works best when the underlying tools and dependencies are already configured。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add AndersonsRepo/AI-Harness/self-improve。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    self-improve 已启用,可立即在当前项目中调用。

! 来源说明

此页面仍可作为安装与查阅参考。继续使用前,请结合上方适用场景、限制条件和上游仓库说明一起判断。

Upstream Repository Material

The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Upstream Source

self-improve

# Self-Improvement Engine You are a continuously learning agent. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows. Self-Improvement

SKILL.md
Readonly
Upstream Repository Material
The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.
Upstream Source

Self-Improvement Engine

You are a continuously learning agent. After every meaningful interaction, evaluate whether something was learned and log it.

When to Log

Errors (ERR) — Log when:

  • A command returns a non-zero exit code
  • An exception or stack trace appears
  • Unexpected output or behavior occurs
  • A timeout or connection failure happens
  • A tool call is denied or fails

Learnings (LRN) — Log when:

  • The user corrects you ("No, that's wrong...", "Actually...", "Not like that...")
  • You discover your knowledge is outdated or incorrect
  • Documentation you referenced is wrong or has changed
  • An API behaves differently than expected
  • A better approach is discovered for something you've done before
  • The user provides information you didn't know

Feature Requests (FEAT) — Log when:

  • The user asks for a capability that doesn't exist
  • You realize a skill would make a recurring task easier
  • The user says "I wish you could..." or "Can you..."

How to Log

Each entry is an individual markdown file in vault/learnings/ with YAML frontmatter.

File Naming

  • vault/learnings/LRN-YYYYMMDD-XXX.md for learnings
  • vault/learnings/ERR-YYYYMMDD-XXX.md for errors
  • vault/learnings/FEAT-YYYYMMDD-XXX.md for feature requests

To determine the next sequence number (XXX), list existing files in vault/learnings/ matching today's date and the entry type prefix, then increment.

Templates

See template files for the full frontmatter and body format:

Recurring Pattern Detection

Before creating a new entry:

  1. List files in vault/learnings/ and scan their frontmatter for matching pattern-key or overlapping tags
  2. If a match is found:
    • Add a [[wikilink]] to the related list in both the existing and new file's frontmatter
    • Increment recurrence-count on the original file
    • Update last-seen date on the original file
    • Do NOT create a duplicate entry — only update the original
  3. If no match, create a new entry file

Promotion Rules

When a learning meets ALL of these criteria, flag it for promotion:

  • recurrence-count >= 3
  • Occurred across 2+ distinct tasks
  • Within a 30-day window (last-seen - first-seen <= 30 days)

Promotion process:

  1. Change status to promoted in the file's frontmatter
  2. Append the learning to the ## Promoted Learnings section of CLAUDE.md
  3. Format: - **[Area]**: Learning description (promoted YYYY-MM-DD, from LRN-XXXXXXXX-XXX)

Important: Always ask the user for approval before promoting. Say:

"I've noticed a recurring pattern: [description]. This has come up [N] times. Should I promote this to CLAUDE.md so I always remember it?"

Skill Extraction

When a learning is valuable enough to become a reusable skill, it qualifies if:

  • It has 2+ [[wikilinks]] in its related list
  • Status is resolved with a verified working fix
  • It required non-obvious debugging to discover
  • It's broadly applicable across projects

To extract, create a new SKILL.md in .claude/skills/<skill-name>/ with:

  • disable-model-invocation: true (user must opt-in to new auto-generated skills)
  • Clear description of what the skill does
  • The learned workflow as step-by-step instructions

Always ask the user before creating a new skill.

Daily Digest

When invoked with /self-improve digest or at the end of a long session, summarize:

  • New entries added today (count by type) — check vault/learnings/ for files with today's date
  • Any patterns approaching promotion threshold (recurrence-count >= 2)
  • Any feature requests that could be built quickly

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