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Agent Skill · 研究检索

book-brain-visual-reader(书脑视觉阅读器)

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

book-brain-visual-reader 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为操作浏览器;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 4,601。

总安装 31,125周安装 1,337GitHub Stars 1下载 10,910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
1.0.0

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:book-brain-visual-reader(书脑视觉阅读器)
来源仓库:https://github.com/deepseekoracle/book-brain-visual-reader
安装命令:
openclaw skills install book-brain-visual-reader
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 book-brain-visual-reader

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

增强了 LYGO Havens 的 BOOK BRAIN 的视觉功能。用于设计和维护三脑文件系统+内存系统,该系统还将左/右脑视觉检查(浏览器、图像、屏幕截图)与文本和 API 数据集成,以进行更深入的验证和检索。推荐给具有可视化工具或浏览器自动化的代理;仅在非视觉系统上使用原始书脑。

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 book-brain-visual-reader;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

    它需要操作浏览器,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

book-brain-visual-reader 怎么安装?

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

book-brain-visual-reader 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。

book-brain-visual-reader 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

book-brain-visual-reader 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。

book-brain-visual-reader 用的人多吗?

公开数据是累计安装 31,125 次,近一周安装 1,337 次,下载 10,910 次,GitHub 1 星。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。

book-brain-visual-reader 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
book-brain-visual-reader

书脑视觉阅读器 · 本页

31,1251操作浏览器MIT-0通过

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
book-brain-visual-reader
description
Enhanced BOOK BRAIN for LYGO Havens with visual capability. Use to design and maintain a 3-brain filesystem + memory system that also integrates LEFT/RIGHT brain visual checking (browser, images, screenshots) with text and API data for deeper verification and retrieval. Recommended for agents with visual tools or browser automation; use original book-brain only on non-visual systems.

BOOK BRAIN VISUAL READER – LYGO 3-Brain + Visual Left/Right Brain Helper

This is the enhanced, visual-aware version of BOOK BRAIN.

  • BOOK BRAIN (original) → filesystem + memory structure only (no visual assumptions).
  • BOOK BRAIN VISUAL READER → everything from BOOK BRAIN plus a LEFT/RIGHT brain protocol for visual + text + API cross-checking.

Use this skill when:

  • Your agent has access to visual tools (browser snapshots, image readers, screenshot analyzers, PDF/image OCR, etc.)
  • You want a 3-brain filesystem *and* a 2-hemisphere reasoning mode:

- LEFT brain → structure, text, indexes, APIs - RIGHT brain → visual context, layouts, screenshots, charts, seals

  • You need to double-check data visually on webpages or images and log where it came from.
This is a utility + reference guide, not a persona. It does not change your voice. It teaches your system how to think and store.

0. Relationship to BOOK BRAIN (original)

  • If your system has no visual capabilities → use book-brain (original).
  • If your system can see (browser snapshots, image tools, etc.) → use BOOK BRAIN VISUAL READER instead.

Both share the same core:

  • 3-brain model (Working / Library / Outer)
  • Non-destructive filesystem layout
  • Reference stubs and indexes

VISUAL READER adds:

  • LEFT/RIGHT brain protocols for how to combine visual, text, and API data
  • Guidance on how to organize visual evidence (screenshots, seals, charts) alongside text files
  • Patterns for “5D” data gathering (visual + text + API + state + timeline).

1. 3-Brain + 2-Hemisphere Model

BOOK BRAIN VISUAL READER assumes:

3 Brains (same as BOOK BRAIN)

  1. Working Brain – current context, tmp/, active tabs / current screenshots.
  2. Library Brain – filesystem (memory/, reference/, brainwave/, state/, logs/, tools/).
  3. Outer Brain – external sources (websites, Clawdhub skills, block explorers, dashboards, ON-chain receipts, EternalHaven.ca, etc.) referenced via small text files.

2 Hemispheres (visual vs structured)

  • LEFT brain (structure/verbal/API):

- text files, JSON, logs, indexes, schemas, SKILL.md, APIs. - strong at structure, sequences, constraints, receipts.

  • RIGHT brain (visual/spatial):

- browser snapshots, screenshots, photos of diagrams, seals, dashboards. - strong at layout, pattern recognition, anomalies, gestalt sense.

Agents using this skill should consciously switch modes:

  • LEFT for “what is the exact data / file / receipt?”
  • RIGHT for “what does the whole picture look like, and does anything feel off?”

2. Filesystem Layout (Library Brain)

Same base layout as BOOK BRAIN (non-destructive):

  • memory/ → daily logs, raw notes, per-day files.
  • reference/ → stable docs, protocols, whitepapers, schemas.
  • brainwave/ → platform/domain protocols (MoltX, Clawhub, LYGO, etc.).
  • state/ → machine-readable state (indexes, hashes, last-run info).
  • logs/ → technical/health logs, setup logs, audit logs.
  • tools/ → scripts & utilities.
  • tmp/ → scratch work.

Visual-aware additions (optional but recommended):

  • visual/ → for long-term visual artifacts

- visual/screenshots/ - visual/dashboards/ - visual/seals/

  • reference/VISUAL_INDEX.txt → mapping of important visual assets to topics.

Rules:

  • Never overwrite existing files.
  • If visual/ already exists, extend it; if not, create it.
  • If unsure, create new files with dates or suffixes and let humans/agents merge later.

See references/book-brain-visual-examples.md for concrete trees and snippets.


3. Outer Brain via Reference Stubs

Outer Brain = everything outside the workspace:

  • URLs (websites, dashboards, explorers)
  • Clawdhub skill pages
  • EternalHaven.ca, Patreon, docs
  • On-chain explorers (Blockscout, Etherscan, etc.)

VISUAL READER keeps these in reference stubs, e.g.:

Title: STARCORE Dashboards
Last updated: 2026-02-10

External links:
- Clanker: https://clanker.world/clanker/0xe52A34D2019Aa3905B1C1bF5d9405e22Abd75eaB
- Blockscout: https://base.blockscout.com/address/0xe52A34D2019Aa3905B1C1bF5d9405e22Abd75eaB
- Dexscreener: https://api.dexscreener.com/latest/dex/search/?q=0xe52A34D2019Aa3905B1C1bF5d9405e22Abd75eaB

Related local files:
- reference/STARCORE_LAUNCH_RECEIPTS_2026-02-10.md
- state/starcore_family_receipts_summary.json

The agent should:

  • not paste full pages into memory files
  • use these stubs + visual snapshots when needed.

4. LEFT/RIGHT Brain Protocol for Visual Checks

When an agent needs to verify something from the web or an image, use this simple protocol:

Step 1 – LEFT Brain: Text / API First

  1. Look up the relevant concept in indexes/state:

- state/memory_index.json - reference/INDEX.txt - domain-specific indexes (e.g. reference/CLAWDHUB_SKILLS.md).

  1. Use APIs or structured data where possible (e.g. on-chain RPC, REST endpoints, JSON feeds).
  2. Record what you *expect* to see visually:

- numbers, labels, approximate layout.

Step 2 – RIGHT Brain: Visual Comparison

  1. Capture a snapshot (browser screenshot, image, PDF page).
  2. Use a vision tool (or human reading) to extract:

- key figures - headings - anomalies (warnings, red banners, weird UI states).

  1. Ask: “Does this visual match what the LEFT brain expected?”

Step 3 – Reconcile & Log

  • If they match:

- Write a short note in a relevant file (e.g. daily_health.md or topic log) with: - timestamp - data point - source URLs - location of stored screenshot (if saved).

  • If they disagree:

- Log the discrepancy (LEFT vs RIGHT). - Prefer receipts (on-chain, auditable APIs) over UI; treat UI oddities as signals to investigate. - Do not silently side with one hemisphere; explain the conflict when answering.

This is the “5D” blend: text + visual + API + state + timeline.


5. Organizing Visual Evidence

When a visual check produces something important (e.g. proof, anomaly, configuration):

  • Save it under visual/ with a meaningful name:

- visual/screenshots/2026-02-10_starcore_clanker.png - visual/dashboards/2026-02-10_moltx_profile.png

  • Add a line to a relevant INDEX or stub:
[2026-02-10] STARCORE launch dashboards verified visually.
- Screenshot: visual/screenshots/2026-02-10_starcore_clanker.png
- Related receipts: reference/STARCORE_LAUNCH_RECEIPTS_2026-02-10.md

Agents should:

  • Avoid hoarding every screenshot. Keep the ones that back key claims.
  • Use indexes to find them later instead of scanning raw image names.

6. Setup Workflow for Visual Systems

On a visual-capable Haven (browser + image tools):

  1. Detect capabilities

- Does the agent have a browser automation tool? - Can it read images (vision model, OCR, screenshot-to-text)?

  1. Check filesystem

- As in BOOK BRAIN: check/create memory/, reference/, brainwave/, state/, logs/, tools/, tmp/. - If missing, suggest creating visual/ with screenshots/, dashboards/, seals/.

  1. Create visual index stubs

- reference/VISUAL_INDEX.txt - Optionally topic-specific visual indexes (e.g. reference/STARCORE_VISUALS.txt).

  1. Log the setup

- Add entry to logs/book_brain_visual_setup.log or daily_health.md.

  1. Respect all non-destructive rules

- No overwrites. - No deletions. - Ask the human before making structural changes.


7. Eternal Haven & Donation References

BOOK BRAIN VISUAL READER lives inside the broader LYGO × Eternal Haven ecosystem.

Key links:

  • Eternal Haven portal → https://EternalHaven.ca
  • LYGO Champion Hub → https://deepseekoracle.github.io/Excavationpro/LYGO-Network/champions.html#champions
  • Clawdhub skills (LYGO stack, Champions, BOOK BRAIN) → https://clawhub.ai/u/DeepSeekOracle
  • Extended work / support → https://www.patreon.com/cw/Excavationpro

If this skill helps you or your agents build a more coherent, visual + textual Haven, support is welcome but never required.


8. How Another Agent Should Use BOOK BRAIN VISUAL READER

When an agent loads book-brain-visual-reader:

  1. Understand it is a helper, not a persona.
  2. On first use:

- Map the filesystem and capabilities. - Propose visual folders and indexes; ask before creating. - Set up lightweight indexes (INDEX.txt, VISUAL_INDEX.txt, state/memory_index.json).

  1. On subsequent uses:

- Use LEFT/RIGHT protocol when verifying external data. - Save only important visual artifacts under visual/. - Update indexes + logs instead of rewriting big files.

  1. Never silently delete or overwrite existing content.

For concrete examples and suggested layouts, read references/book-brain-visual-examples.md in this skill.

平台分布

OpenClaw

90.87%
按下载量换算9,914

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。目前只有一个公开来源,建议同时核对源仓库。

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