| name | self-improving-agent |
| description | Cursor 版自进化技能：把会话中的有效经验沉淀为可复用知识。支持记忆体检、规则晋升、技能提取与显式记忆写入。适用场景：复盘近期改动、把高频模式升级为规则、把排障方案抽成技能、治理记忆冗余与过期内容。 |
Self-Improving Agent (Cursor Edition)
Capture -> Curate -> Enforce -> Reuse
本技能用于 Cursor 编辑器中的 Agent 工作流：将临时经验持续沉淀为长期有效的工程知识，并把高价值方案转化为规则或独立技能。
目标与边界
- 目标
- 识别高频、稳定、可验证的做法
- 将做法晋升为项目规则或可复用技能
- 控制记忆体噪声，避免上下文浪费
- 非目标
- 不为一次性临时方案建立永久规则
- 不把未经验证的猜测写入长期记忆
- 不替代正常代码评审和测试
在 Cursor 中何时触发
满足任一条件时应主动触发本技能：
- 刚完成一次复杂改造或排障，且有可复用结论
- 同类问题在近几次会话重复出现 2 次以上
- 发现现有规则与实际代码习惯不一致
- 记忆文件明显膨胀，出现过期路径、失效约定或重复条目
Cursor 适配的知识分层
在 Cursor 项目中按短期到长期管理知识：
- 会话上下文（短期）
- 当前对话与编辑历史中的即时结论
- 用于当前任务推进，不默认长期保留
- 项目规则（长期、强约束）
- 放入项目级规则文件（如
.cursorrules 或团队约定文件）
- 只收录稳定、可执行、可验证的规则
- 可复用技能（长期、可迁移）
- 以
SKILL.md + 示例 + 参考文档 形式沉淀
- 面向跨项目复用的模式化方案
核心流程（Cursor Agent 执行）
1) Review：记忆体检
输入：
- 最近完成的任务、错误修复、重构记录
- 相关记忆文件与规则文件
检查维度：
- 重复出现：是否跨会话、跨文件反复出现
- 稳定性：是否适用于主干场景，而非一次性例外
- 可验证性：是否可通过 lint、test、build 或运行结果证明
- 维护成本：是否会增加认知负担或误导后续修改
输出：
- 可晋升候选（建议进入规则）
- 可提取候选（建议生成技能）
- 待删除或待合并条目（降噪）
2) Promote：规则晋升
准入标准（全部满足）：
- 至少 2 次真实场景验证
- 能写成明确应当/禁止语句
- 与现有规则不冲突，或已合并冲突条目
落地要求：
- 使用简洁、可执行语言
- 每条规则只表达一个核心约束
- 添加最小必要示例，避免长篇解释
3) Extract：技能提取
当某方案具备可复用步骤、明确输入输出、常见陷阱时，提取为独立技能：
- 必备结构
SKILL.md：用途、触发条件、步骤、验收标准references/：关键背景资料或链接examples/：至少 1 个正例和 1 个边界例
4) Remember：显式记忆写入
仅在以下情况写入：
- 该信息会显著提升后续任务成功率
- 该信息短期内会被频繁复用
- 当前规则层尚未覆盖此知识点
决策矩阵
同一条经验应放在哪里：
- 放规则文件：稳定、通用、必须遵守
- 放技能：步骤化、可迁移、可复用的解决方案
- 放临时记忆：尚在观察期，证据不足
质量门禁（执行后自检）
每次执行本技能后，至少确认：
- 新增规则是否与现有规则重复或冲突
- 提取出的技能是否可被第三方直接理解并复现
- 记忆清理是否误删仍在使用的上下文
- 是否保留必要证据（命令结果、错误特征、验证方式）
输出模板（建议）
A. Review 报告
- 候选晋升规则（含理由）
- 候选提取技能（含收益）
- 待清理条目（含风险提示）
B. Promote 结果
- 新增/更新规则列表
- 冲突处理说明
- 验证结果（lint/test/build）
C. Extract 结果
迁移说明（从 Claude Code 版本到 Cursor）
- 不再依赖
/si:* 指令体系
- 不再依赖 Claude 插件安装流程
- 保留原有 review/promote/extract/remember 能力，但改为 Cursor Agent 的任务步骤与产物约束
反模式（避免）
- 把一次性 bug workaround 直接写成长期规则
- 将风格偏好伪装成工程约束
- 技能文档缺少输入输出，导致不可复现
- 只记录结论，不保留验证证据
最小执行清单
name: "self-improving-agent"
description: "Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity."
Self-Improving Agent
Auto-memory captures. This plugin curates.
Claude Code's auto-memory (v2.1.32+) automatically records project patterns, debugging insights, and your preferences in MEMORY.md. This plugin adds the intelligence layer: it analyzes what Claude has learned, promotes proven patterns into project rules, and extracts recurring solutions into reusable skills.
Quick Reference
| Command | What it does |
|---|
/si:review | Analyze MEMORY.md — find promotion candidates, stale entries, consolidation opportunities |
/si:promote | Graduate a pattern from MEMORY.md → CLAUDE.md or .claude/rules/ |
/si:extract | Turn a proven pattern into a standalone skill |
/si:status | Memory health dashboard — line counts, topic files, recommendations |
/si:remember | Explicitly save important knowledge to auto-memory |
How It Fits Together
┌─────────────────────────────────────────────────────────┐
│ Claude Code Memory Stack │
├─────────────┬──────────────────┬────────────────────────┤
│ CLAUDE.md │ Auto Memory │ Session Memory │
│ (you write)│ (Claude writes)│ (Claude writes) │
│ Rules & │ MEMORY.md │ Conversation logs │
│ standards │ + topic files │ + continuity │
│ Full load │ First 200 lines│ Contextual load │
├─────────────┴──────────────────┴────────────────────────┤
│ ↑ /si:promote ↑ /si:review │
│ Self-Improving Agent (this plugin) │
│ ↓ /si:extract ↓ /si:remember │
├─────────────────────────────────────────────────────────┤
│ .claude/rules/ │ New Skills │ Error Logs │
│ (scoped rules) │ (extracted) │ (auto-captured)│
└─────────────────────────────────────────────────────────┘
Installation
Claude Code (Plugin)
/plugin marketplace add alirezarezvani/claude-skills
/plugin install self-improving-agent@claude-code-skills
OpenClaw
clawhub install self-improving-agent
Codex CLI
./scripts/codex-install.sh --skill self-improving-agent
Memory Architecture
Where things live
| File | Who writes | Scope | Loaded |
|---|
./.cursorrules | You (+ promote step) | Project rules | Full file, every session |
./.cursor/rules/*.md | You (+ promote step) | Scoped rules | When matching files are in context |
./.agents/skills/**/SKILL.md | You/Agent (extract step) | Reusable workflows | On demand when skill is invoked |
| Session context (Cursor Agent) | Agent runtime | Temporary learnings | Current conversation only |
./docs/knowledge/*.md (optional) | You/Agent | Team-shared durable notes | On demand |
The promotion lifecycle
1. Claude discovers pattern → auto-memory (MEMORY.md)
2. Pattern recurs 2-3x → /si:review flags it as promotion candidate
3. You approve → /si:promote graduates it to CLAUDE.md or rules/
4. Pattern becomes an enforced rule, not just a note
5. MEMORY.md entry removed → frees space for new learnings
Core Concepts
Auto-memory is capture, not curation
Auto-memory is excellent at recording what Claude learns. But it has no judgment about:
- Which learnings are temporary vs. permanent
- Which patterns should become enforced rules
- When the 200-line limit is wasting space on stale entries
- Which solutions are good enough to become reusable skills
That's what this plugin does.
Promotion = graduation
When you promote a learning, it moves from Claude's scratchpad (MEMORY.md) to your project's rule system (CLAUDE.md or .claude/rules/). The difference matters:
- MEMORY.md: "I noticed this project uses pnpm" (background context)
- CLAUDE.md: "Use pnpm, not npm" (enforced instruction)
Promoted rules have higher priority and load in full (not truncated at 200 lines).
Rules directory for scoped knowledge
Not everything belongs in CLAUDE.md. Use .claude/rules/ for patterns that only apply to specific file types:
---
paths:
- "src/api/**/*.test.ts"
- "tests/api/**/*"
---
- Use supertest for API endpoint testing
- Mock external services with msw
- Always test error responses, not just happy paths
This loads only when Claude works with API test files — zero overhead otherwise.
Agents
memory-analyst
Analyzes MEMORY.md and topic files to identify:
- Entries that recur across sessions (promotion candidates)
- Stale entries referencing deleted files or old patterns
- Related entries that should be consolidated
- Gaps between what MEMORY.md knows and what CLAUDE.md enforces
skill-extractor
Takes a proven pattern and generates a complete skill:
- SKILL.md with proper frontmatter
- Reference documentation
- Examples and edge cases
- Ready for
/plugin install or clawhub publish
Hooks
error-capture (PostToolUse → Bash)
Monitors command output for errors. When detected, appends a structured entry to auto-memory with:
- The command that failed
- Error output (truncated)
- Timestamp and context
- Suggested category
Token overhead: Zero on success. ~30 tokens only when an error is detected.
Platform Support
| Platform | Memory System | Plugin Works? |
|---|
| Claude Code | Auto-memory (MEMORY.md) | ✅ Full support |
| OpenClaw | workspace/MEMORY.md | ✅ Adapted (reads workspace memory) |
| Codex CLI | AGENTS.md | ✅ Adapted (reads AGENTS.md patterns) |
| GitHub Copilot | .github/copilot-instructions.md | ⚠️ Manual promotion only |
Related
