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eternal-adaptive-brain永恒的适应性大脑

Agent Skill

eternal-adaptive-brain 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。

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2,920

周安装

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下载量

945
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:eternal-adaptive-brain(永恒的适应性大脑)
来源仓库:https://github.com/eternal0404/eternal-adaptive-brain
安装命令:
openclaw skills install eternal-adaptive-brain
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 eternal-adaptive-brain

简介

自适应自我改进智能体大脑,可检测模式、预测故障、适应行为、发展技能并跟踪一段时间内的表现。

SKILL.md

name
adaptive-brain
description
Adaptive self-improving agent brain that learns, evolves, and optimizes itself over time. Use when you need: performance tracking, error pattern detection, automatic behavior adaptation, skill evolution, confidence-weighted learning, rollback on bad changes, metrics dashboards, proactive failure prediction, or cross-session memory synthesis. Triggers on "self improve", "learn from mistakes", "track performance", "evolve behavior", "adaptive agent", "improve yourself", "what did you learn", "learning dashboard", or when errors/corrections are detected.

Adaptive Brain

A self-improving agent system that doesn't just log — it learns, adapts, and evolves.

Core Philosophy

The existing self-improving-agent skill logs to markdown. That's a diary. This is an immune system — it detects patterns, builds antibodies, prevents recurring failures, and gets smarter with every interaction.

Quick Start

python3 scripts/brain.py init          # Initialize brain system
python3 scripts/brain.py learn         # Log a learning
python3 scripts/brain.py error         # Log an error
python3 scripts/brain.py adapt         # Run adaptation cycle
python3 scripts/brain.py dashboard     # Show improvement metrics
python3 scripts/brain.py predict "task description"  # Predict failure risk
python3 scripts/brain.py evolve        # Auto-evolve skill configs

What Makes This Different

FeatureBasic LoggerAdaptive Brain
Log entries
Pattern detection✅ Recurring error clustering
Confidence scoring✅ Weighted by success rate
Auto-adaptation✅ Changes behavior automatically
Failure prediction✅ Risk scoring before tasks
Skill evolution✅ Rewrites SKILL.md based on learnings
Rollback✅ Reverts bad adaptations
Performance metrics✅ Tracks improvement over time
Cross-pattern links✅ Connects related errors
Behavioral DNA✅ Encodes successful patterns
Outcome tracking✅ Tracks prediction accuracy
Skill mutation✅ Auto-generates prevention rules
Context awareness✅ Weighs learnings by recency & area
Feedback loop✅ Confirms/contradicts based on outcomes

Architecture

~/.adaptive-brain/
├── brain.json          # Core state: DNA, confidence, metrics
├── learnings.json      # All learnings with scores and links
├── patterns.json       # Detected recurring patterns
├── evolution.json      # History of adaptations and rollbacks
├── metrics.json        # Performance tracking over time
└── predictions.json    # Failure predictions and outcomes

Commands

learn — Log a learning with auto-classification

python3 scripts/brain.py learn \
  --type correction \
  --summary "User corrected: weather defaults to UTC not local" \
  --area config \
  --context "Asked for Dhaka weather, got UTC time" \
  --fix "Always check USER.md timezone before reporting weather"

error — Log an error with pattern detection

python3 scripts/brain.py error \
  --command "pip install pandas" \
  --error "externally-managed-environment" \
  --fix "Use venv or --break-system-packages" \
  --files "signal_engine.py"

The brain automatically checks for similar past errors and links them.

adapt — Run adaptation cycle

Scans recent learnings and errors, then:

  1. Detects recurring patterns (same error 3+ times)
  2. Updates behavioral DNA
  3. Generates prevention rules
  4. Optionally promotes to workspace files

predict — Predict failure risk before a task

python3 scripts/brain.py predict "deploy to production"

Returns risk score based on:

  • Past errors in similar tasks
  • Confidence level in relevant skills
  • Historical success rate for task type

evolve — Auto-evolve based on accumulated learnings

python3 scripts/brain.py evolve

The brain reviews all learnings and:

  1. Identifies patterns that should become permanent rules
  2. Generates optimized SKILL.md patches
  3. Creates behavioral DNA mutations
  4. Tracks evolution history (for rollback)

dashboard — Learning metrics

Shows:

  • Total learnings by category
  • Error recurrence rate
  • Adaptation success rate
  • Improvement trend (getting better or worse?)
  • Top patterns
  • Confidence score over time

rollback — Undo a bad adaptation

python3 scripts/brain.py rollback --to 3

Reverts to a previous evolution state.

Behavioral DNA

The brain maintains a "DNA" string encoding successful behavioral patterns:

{
  "dna": {
    "always_use_venv": true,
    "check_prices_before_trade": true,
    "write_files_then_execute": true,
    "test_before_publish": true,
    "default_timezone": "UTC"
  },
  "mutations": [
    {"timestamp": "...", "gene": "always_use_venv", "reason": "3 pip errors in a row"}
  ]
}

Each gene is backed by learnings. When a gene's backing learnings are resolved, it can be retired.

Pattern Detection

The brain clusters errors and learnings into patterns:

{
  "patterns": [
    {
      "id": "P001",
      "name": "Package install failures",
      "keywords": ["pip", "externally-managed", "venv"],
      "count": 4,
      "first_seen": "2026-03-30",
      "last_seen": "2026-03-31",
      "prevention": "Always use venv or --break-system-packages",
      "confidence": 0.95
    }
  ]
}

Integration with OpenClaw

The brain reads and writes to workspace files:

Brain ActionTarget FileWhen
Behavioral ruleSOUL.mdConfidence > 0.9, seen 3+ times
Tool gotchaTOOLS.mdError pattern for specific tool
WorkflowAGENTS.mdProcess improvement confirmed
Long-termMEMORY.mdMajor insight or decision

Learning Confidence

Every learning has a confidence score (0-1) that changes over time:

  • New learning: 0.5 (neutral)
  • Confirmed correct: +0.2 per successful application
  • Contradicted: -0.3
  • Resolves error: +0.1
  • Older than 30 days: decays by 0.1

Only high-confidence learnings (>0.8) get promoted to workspace files.

Automatic Triggers

After each session, the brain should run:

python3 scripts/brain.py adapt

Or set up a cron job:

Schedule: daily at 23:00
Command: python3 scripts/brain.py adapt

See Also

For basic markdown logging (complementary to this skill), see the self-improving-agent skill. This skill is an enhanced superset with adaptation, prediction, and evolution capabilities.

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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