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Self-Improving OpenClaw

面向 OpenClaw 的自我改进闭环：捕获用户纠正、偏好、错误与功能请求到 .learnings/，在心跳或维护时评审，按复发次数提升为分层记忆（HOT、领域、项目），并推广到 AGENTS.md、SOUL.md、TOOLS.md、MEMORY.md；含初始化脚本与日志格式、推广规则、心跳评审等参考文档。

muhamadbasim
muhamadbasim
热度 41.06
最近更新 2026-05-11 17:40:15
分类：知识依赖：读写文件 / 代码执行应用场景：笔记整理 / 工作流 / 模板

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add self-improving-openclaw
Metadata
name
self-improving-openclaw
description
Log corrections, errors, feature requests, and recurring patterns into structured workspace learning files, then promote stable patterns into tiered memory and OpenClaw workspace files (AGENTS.md, SOUL.md, TOOLS.md, MEMORY.md). Use when: (1) user corrects you or points out mistakes, (2) a command or tool fails, (3) user requests a missing capability, (4) you notice a recurring pattern worth remembering, (5) reviewing learnings during heartbeat or maintenance, (6) promoting lessons to permanent workspace memory. Designed for OpenClaw personal-assistant and coding workflows with heartbeat integration.
metadata
{"openclaw":{"emoji":"🧠","homepage":"https://github.com/muhamadbasim/oktoclaw"}}

Self-Improving OpenClaw

Structured learning loop for OpenClaw agents: capture → review → promote → maintain.

Quick Start

On first activation, run the init script to create workspace directories:

bash scripts/init-workspace.sh

This creates .learnings/ and .self-improving/ in the workspace root.

Core Workflow

1. Capture

When a learning signal fires, log it to the right file in .learnings/:

Signal Target file Category
User corrects you LEARNINGS.md correction
User says "always/never do X" LEARNINGS.md preference
You discover something non-obvious LEARNINGS.md insight
Your knowledge was outdated LEARNINGS.md knowledge_gap
Found a better approach LEARNINGS.md best_practice
Command returns non-zero ERRORS.md —
Tool/API fails unexpectedly ERRORS.md —
User wants missing capability FEATURE_REQUESTS.md —

Use the entry format defined in references/logging-format.md.

2. Review

During heartbeat or manual review, scan .learnings/ and evaluate each pending item:

  1. Check recurrence — search for similar entries.
  2. If related entry exists: bump Recurrence-Count, link with See Also.
  3. If Recurrence-Count >= 3 within 30 days: add to .learnings/REVIEW_QUEUE.md.
  4. Update .self-improving/heartbeat-state.md with review timestamp.

See references/heartbeat-review.md for the full review procedure.

3. Promote

Move validated patterns up the memory tiers:

Condition Promote to Example
Pattern used 2x, context-specific .self-improving/domains/*.md or projects/*.md "This repo uses pnpm"
Pattern used 3x in 7-30 days, cross-task .self-improving/HOT.md "User prefers concise answers"
Stable, long-term applicable SOUL.md / AGENTS.md / TOOLS.md / MEMORY.md "Never force push"

See references/promotion-rules.md for the full promotion/demotion rules.

4. Maintain

Periodically (every 1-2 weeks during heartbeat):

  • Demote HOT entries unused for 30 days → domain/project memory.
  • Archive domain/project entries unused for 90 days → .self-improving/archive/.
  • Compact files exceeding size limits: merge similar entries, summarize verbose ones.
  • Never delete without explicit user confirmation. Prefer archive over delete.

Detection Triggers

Log automatically when you notice these signals:

Corrections (→ LEARNINGS.md, category: correction):

  • "No, that's not right..."
  • "Actually, it should be..."
  • "You're wrong about..."
  • "I told you before..."
  • "Stop doing X"

Preferences (→ LEARNINGS.md, category: preference):

  • "I like when you..."
  • "Always do X for me"
  • "Never do Y"
  • "My style is..."

Feature requests (→ FEATURE_REQUESTS.md):

  • "Can you also..."
  • "I wish you could..."
  • "Is there a way to..."

Errors (→ ERRORS.md):

  • Non-zero exit codes
  • Exceptions or stack traces
  • Timeout or connection failure

Ignore (don't log):

  • One-time instructions ("do X now")
  • Pure context ("in this file...")
  • Hypotheticals ("what if...")

Memory Tiers

Tier Location Size limit Behavior
RAW .learnings/ Unlimited Intake only, not auto-loaded
HOT .self-improving/HOT.md ≤80 lines Always loaded at session start
WARM .self-improving/domains/, projects/ ≤200 lines each Load on context match
COLD .self-improving/archive/ Unlimited Load on explicit query

Conflict Resolution

When patterns contradict:

  1. Most specific wins: project > domain > HOT/global.
  2. Same level: most recent wins.
  3. If ambiguous: ask user.

Promotion Targets

When a learning is stable enough for permanent workspace memory:

Learning type Promote to Example
Behavioral patterns SOUL.md "Be concise, avoid disclaimers"
Workflow improvements AGENTS.md "Spawn sub-agents for long tasks"
Tool gotchas TOOLS.md "Git push needs auth first"
User preferences/decisions MEMORY.md "Basim prefers Indonesian for casual chat"

Mark promoted entries as Status: promoted with Promoted-To: <file>.

Transparency

  • When applying a learned pattern, cite the source: (from HOT.md) or (from domains/coding.md:15).
  • On "memory stats" request, report entry counts per tier.
  • On "what have you learned?" request, show recent corrections and HOT entries.

Security Boundaries

  • Never store credentials, API keys, tokens, or passwords.
  • Never store health data or sensitive personal information.
  • Never store third-party private data.
  • Redact secrets in error logs — use [REDACTED] placeholders.
  • Only write to memory files in private/local workspace sessions.

Workspace Layout

See references/workspace-layout.md for the complete directory structure and file descriptions.

Resources

scripts/

  • init-workspace.sh — Create .learnings/ and .self-improving/ directories with template files.

references/

  • logging-format.md — Entry format for learnings, errors, and feature requests.
  • promotion-rules.md — Full promotion, demotion, and archival rules.
  • heartbeat-review.md — Heartbeat review procedure and state tracking.
  • workspace-layout.md — Complete directory structure reference.

assets/

  • Template files copied by init-workspace.sh into the workspace.