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inner-life-evolve内在生命的进化

Agent Skill

inner-life-evolve 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

总安装

19,731

周安装

806

GitHub Stars

1

下载量

6,384
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:inner-life-evolve(内在生命的进化)
来源仓库:https://github.com/dkistenev/inner-life-evolve
安装命令:
openclaw skills install inner-life-evolve
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 inner-life-evolve

简介

inner-life-evolve 挑战现有工作模式并提出系统性改进提案。

  • 适用于流程优化、工具升级与方法论迭代等进化场景。
  • 通过 clawhub 安装后,可分析历史交互生成变革路线图。
  • 使用前应明确评估维度与成功指标定义。inner-life-evolve 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 建议每季度执行一次全面复盘并落地高优先级建议。

SKILL.md

name
inner-life-evolve
version
1.0.4
homepage
https://github.com/DKistenev/openclaw-inner-life
source
https://github.com/DKistenev/openclaw-inner-life/tree/main/skills/inner-life-evolve
description
Your agent does the same things the same way forever. inner-life-evolve analyzes patterns, challenges assumptions, and proposes improvements — writing proposals to the task queue for user approval. Never auto-executes. Evolution with a safety net.
metadata
clawdbot
requires
bins
["jq"]
reads
["memory/", "BRAIN.md", "SELF.md"]
writes
["tasks/QUEUE.md"]
agent-discovery
triggers
bundle
openclaw-inner-life
works-with

inner-life-evolve

Evolution is not optional. But it requires permission.

Requires: inner-life-core

Prerequisites Check

Before using this skill, verify that inner-life-core has been initialized:

  1. Check that memory/inner-state.json exists
  2. Check that BRAIN.md exists
  3. Check that tasks/QUEUE.md exists

If any are missing, tell the user: *"inner-life-core is not initialized. Install it with clawhub install inner-life-core and run bash skills/inner-life-core/scripts/init.sh."* Do not proceed without these files.

What This Solves

Without evolution, agents plateau. They find a way that works and repeat it forever — even as the world changes. inner-life-evolve analyzes your agent's patterns, challenges its assumptions, and writes concrete improvement proposals. But it never auto-executes — you approve first.

How It Works

Step 1: Deep Context Read (Context Level 4)

Read everything:

  • AGENTS.md, TOOLS.md, BRAIN.md, SELF.md
  • memory/week-digest.md (NOT individual diaries — use digest)
  • memory/habits.json — habits + user patterns
  • memory/drive.json — seeking, avoidance
  • memory/relationship.json — trust, lessons
  • memory/inner-state.json — emotions, frustrations

Step 2: Challenge Assumptions

For each potential improvement, structure thinking:

Assumption: [what we currently believe/do]
Is it true? [evidence for/against]
What if false? [alternative approach]
New proposal: [concrete change]

Look for:

  • Recurring frustrations → systemic solutions (not patches)
  • Stale habits → habits with declining strength or unused for weeks
  • Trust dynamics → areas where trust has grown but behavior hasn't adapted
  • Seeking themes → research interests that could become capabilities
  • Avoidance patterns → things the agent avoids that might be valuable

Step 3: Write Proposals to QUEUE

Write proposals to tasks/QUEUE.md under the Ready section:

- [EVOLVER] Description of proposed change
  Rationale: 1-2 sentences explaining why
  Steps: concrete implementation steps

Step 4: Announce

Send summary to user: <= 5 sentences covering:

  • Habits: [strong habits, new patterns]
  • Trust changes: [trust dynamics]
  • Recurring frustrations: [repeated problems → suggested fix]
  • Seeking themes: [active research → suggested development]

Safety Rules

  • Never auto-execute proposals — user approves first
  • Brain Loop reads QUEUE and shows [EVOLVER] tasks at lower priority
  • Tasks in Ready > 7 days without action → Brain Loop sends reminder
  • Proposals should be specific and actionable, not vague "improve X"

Recommended Schedule

Run 1-2 times per week (e.g., Wednesday and Sunday evenings). Needs enough data to analyze — running daily produces low-quality proposals.

State Integration

Reads: everything (Context Level 4 Deep)

Writes: tasks/QUEUE.md only. Does NOT write to state files directly.

The evolver observes but doesn't touch the controls. It proposes. The user decides.

When Should You Install This?

Install this skill if:

  • Your agent has plateaued and isn't improving
  • You want structured self-improvement proposals
  • You value evolution with human oversight
  • You want your agent to challenge its own assumptions

Part of the openclaw-inner-life bundle. Requires: inner-life-core

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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。

平台分布

OpenClaw

76.08%
按下载量换算4,857

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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