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Agent Skill · 开发

subconscious(subconscious 开发)

subconscious 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。

subconscious 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 7,954。

总安装 3,427周安装 140GitHub Stars 公开资料未说明下载 1,098核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.8.0

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:subconscious(subconscious 开发)
来源仓库:https://github.com/elyasdruid/subconscious
安装命令:
openclaw skills install subconscious
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 subconscious

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

该技能作为自主偏差层,用于管理与强化 Agent 的自我改进学习机制。通过记录错误与经验缺口,不断优化操作行为与决策逻辑,提升长期适应性。安装前需确认是否允许修改内部记忆结构与策略参数,注意系统稳定性影响。输出为隐式行为调整,不直接返回结果,需结合其他技能观察效果变化。

适用于高级 Agent 调优场景,普通用户建议谨慎启用以防意外行为。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install subconscious;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

subconscious 怎么安装?

在终端执行 openclaw skills install subconscious。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

subconscious 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

subconscious 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

subconscious 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

subconscious 用的人多吗?

公开数据是累计安装 3,427 次,近一周安装 140 次,下载 1,098 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

subconscious 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
subconscious

subconscious 开发 · 本页

3,427—调用外部服务MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
subconscious
description
A bounded, governed self-improvement layer for OpenClaw agents. Consumes learnings from the self-improving-agent skill (produces .learnings/), evolves them through a typed mutation system, and surfaces emerging behavioral patterns as session biases. Triggers on: subconscious system installation, health checks, metabolism management (tick/rotate/review/benchmark), or reviewing what biases are active. Do NOT invoke proactively — only when Edward specifically asks about it or when the system health check cron reports issues.
readme
README.md
metadata
version
1.6
compatibility
openclaw
>= 1.0.0
tags
category
agent-framework
license
MIT
author
elyasdruid
homepage
https://clawhub.ai/skills/subconscious
repositories
url
https://github.com/elyasdruid/subconscious

Subconscious v1.5 — Bounded Self-Improving Agent

What It Is

A persistent, self-evolving bias layer that survives session resets. Alfred's "second brain" — quiet, bounded, and strictly governed. It does NOT make decisions. It shapes how Alfred *approaches* decisions.

Core principle: Every mutation is typed, bounded, and logged. Core identity is untouchable without manual override.

Architecture

Learnings Bridge          Pending Queue           Live Store           Session Context
.learnings/ ─────────────► tick ──────────────► rotate ──────────────► bias inject
(Self-improving agent)    (reinforce,           (promote eligible,       (5 items max,
                         dedupe,               archive stale)           ephemeral)
                         skip duplicates)

Core Store ────────────────────────────────────────────────────────────────► Identity
(Immutable values,                                                  (never changes
 values/style, guiding principles)                                   without human OK)

Three layers:

  • core/ — Immutable identity (Alfred's nature, Edward's preferences). Manual-only.
  • live/ — Active learnings from experience. Governed promotion from pending.
  • pending/ — Queue for new items. Bounded reinforcement before promotion eligibility.

Five bias types:

KindCategoryExample
VALUEIdentity"Alfred is sharp, calm, direct"
LESSONContext"XHS MCP needs QR re-login each cycle"
PRIORITYActive"Verify before claiming success"
PATTERNInterpretation"Proof discipline failure mode"
CONSTRAINTAttention"Don't suggest without trying first"

Lifecycle Commands

All commands run from scripts/ directory inside the skill:

cd ~/.openclaw/skills/subconscious/scripts

# Check system health
python3 subconscious_metabolism.py status
python3 subconscious_cli.py verify

# See active biases in session context
python3 subconscious_cli.py bias

# Manual metabolism cycles
python3 subconscious_metabolism.py tick        # Light tick (5 min cadence)
python3 subconscious_metabolism.py rotate       # Full rotation (hourly)
python3 subconscious_metabolism.py review       # Daily health check

Metabolism Cycles

Tick (every 5 min)

python3 subconscious_metabolism.py tick
  • Scans .learnings/ via learnings bridge → queues new items to pending
  • Passive reinforcement: increments reinforcement count on pending items
  • Skips already-reinforced items (prevents type corruption)
  • Runs bounded maintenance: freshness decay, metrics, no structural changes

Rotate (hourly)

python3 subconscious_metabolism.py rotate --enable-promotion
  • Full maintenance: flush, decay, snapshot rotation
  • Promotion gate (only with --enable-promotion):

- confidence >= 0.75 - reinforcement >= 3 - freshness >= 0.3 - Not a duplicate of anything in core/live/pending - Passes governance check

  • Governance enforces typed mutation bounds on all items

Review (daily at 6am)

python3 subconscious_metabolism.py review
  • System health check
  • Snapshot integrity
  • Pending queue depth check
  • Recommendations log

Learnings Bridge

The learnings bridge connects the self-improving-agent skill to the subconscious:

  • Scans .learnings/LEARNINGS.md, .learnings/ERRORS.md, .learnings/FEATURES.md
  • Tracks seen entries per file in learnings_bridge_last_seen.json
  • New entries → queued to pending.jsonl with type candidate_queued
  • Entries already reinforced in this session → skipped (idempotent)

Bridge to self-improving agent: The learnings bridge should be called from the metabolism tick so that new learnings flow into the subconscious every 5 minutes automatically.

Checking System Health

python3 subconscious_metabolism.py status

Expected output:

Core: 3/50   Live: 1/100   Pending: 0/500   Snapshots: 10/10
Status: OK

If Pending: 0/500 and Live: N — system is healthy, items promoting correctly. If Status: blocked — resource limits hit, run rotate to compact.

Adding Items Manually

# Queue a lesson manually
python3 subconscious_cli.py intake --kind LESSON --text "Remember to verify before claiming success" --confidence 0.8 --source "manual"

# Check what's in pending
python3 subconscious_cli.py pending

Key Files

FilePurpose
subconscious/schema.pyItem dataclasses, validation, kind enum
subconscious/store.pyJSON file ops with atomic writes
subconscious/retrieve.pyRelevance scoring, is_duplicate
subconscious/influence.pyConvert items to bias blocks for prompts
subconscious/governance.pyMutation types, protection classes, bounds
subconscious/evolution.pyPromotion pipeline, reinforcement logic
subconscious/maintenance.pyDecay, snapshot rotation, housekeeping
subconscious/intake.pyConservative item extraction from turns
subconscious/flush.pySnapshot building/loading for session continuity
subconscious/learnings_bridge.pyBridge to self-improving-agent .learnings/

For Claude Code Sessions

When Claude Code needs to assess or improve the subconscious system, use the claude-cx wrapper:

claude-cx "Run: python3 ~/.openclaw/skills/subconscious/scripts/subconscious_metabolism.py status"
claude-cx "Run: python3 ~/.openclaw/skills/subconscious/scripts/subconscious_cli.py bias"
claude-cx "Read ~/.openclaw/skills/subconscious/subconscious/evolution.py lines 450-525"

Cron Setup

After running install.sh, four cron jobs are active:

  • */5 * * * * — tick (light metabolism)
  • 0 * * * * — rotate (hourly, with promotion)
  • 0 6 * * * — review (daily health check)
  • 0 9 * * 1 — weekly benchmark (Monday 9am, compares to baseline)

Weekly Benchmark

Compares current state to the baseline snapshot captured at install time. Reports on:

  • Learnings volume change (LEARNINGS.md, ERRORS.md entries)
  • New biases promoted to live
  • Pending queue depth
  • Error recurrence as a proxy for learning effectiveness
# Run manually
python3 scripts/subconscious_benchmark.py

# View past benchmarks
ls memory/subconscious/benchmarks/
cat memory/subconscious/benchmarks/benchmark_YYYY-MM-DD.json

To capture a new baseline:

python3 scripts/subconscious_benchmark.py --capture-baseline

To override workspace location:

export SUBCONSCIOUS_WORKSPACE=/path/to/any/workspace

平台分布

OpenClaw

91.9%
按下载量换算1,009

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

可疑

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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