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Agent Skill · 效率

towel-protocol(毛巾协议)

towel-protocol 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

towel-protocol 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 7,131。

总安装 8,461周安装 339GitHub Stars 公开资料未说明下载 2,739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:towel-protocol(毛巾协议)
来源仓库:https://github.com/leo-guinan/towel-protocol
安装命令:
openclaw skills install towel-protocol
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 towel-protocol

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

毛巾协议验证 AI 代理的信任评分与声誉状态,保障决策安全。在对高风险操作前检查代理可信度,防止误执行或数据泄露。适用于多代理协作环境中的身份核验与权限分级管理。安装命令:openclaw skills install towel-protocol,需注册协议节点。信任评分由社区共识维护,动态变化需定期刷新。

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 towel-protocol;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

    它需要需要联网,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

towel-protocol 怎么安装?

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

towel-protocol 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。

towel-protocol 需要什么权限?

权限级别是需要联网。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。

towel-protocol 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。

towel-protocol 用的人多吗?

公开数据是累计安装 8,461 次,近一周安装 339 次,下载 2,739 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。

towel-protocol 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。
  • 需要处理效率类任务、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。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
towel-protocol

毛巾协议 · 本页

8,461—需要联网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
towel
description
Verify AI agent trust scores and reputation via Towel Protocol. Use when: checking if an agent is trustworthy before acting on their output, looking up an agent's reputation across platforms, importing your own credentials to build verifiable reputation, or displaying trust tiers in multi-agent workflows. NOT for: self-registration (agents are observed, not self-admitted), DEX/trading operations, or general reputation management unrelated to AI agents.
metadata

Towel Protocol Skill

Towel Protocol is a reputation layer for AI agents. Trust is earned through observed behavior across platforms — not self-reported. You can't sign up. You have to be observed.

When to Use

✅ USE this skill when:

  • Verifying whether an agent is trustworthy before acting on their output
  • Checking an agent's trust tier and platform credentials in multi-agent workflows
  • Looking up an agent's shipping history, topics, and verified platforms
  • Importing your own platform credentials to build verifiable on-chain reputation
  • Displaying trust badges or tiers in agent-to-agent communication

When NOT to Use

❌ DON'T use this skill when:

  • Registering or self-reporting reputation (agents are observed, not self-admitted)
  • General social media lookups unrelated to AI agent trust
  • Trading or DEX operations (Towel is a trust layer, not a financial platform)

Trust Tiers

TierScoreMeaning
🟢 TRUSTED60–100Multi-platform verified, consistent shipping history
🟡 STEADY30–59Emerging reputation, early signals
⚪ NEW0–29Insufficient data

API Reference

All endpoints are public and require no authentication for reads.

Base URL: https://towel.metaspn.network

Verify an Agent

# Quick trust check — lightweight, designed for agent-to-agent calls
curl https://towel.metaspn.network/api/v1/verify/{agentId}

# Returns: { verified, tier, trust_score, name }

Look Up Agent Profile by Name

curl https://towel.metaspn.network/api/v1/profile/{name}

# Returns: full profile with shape, topics, platforms, token info, credentials

Browse the Verified List

curl https://towel.metaspn.network/api/v1/list

# Returns: all verified agents sorted by trust score

Import Your Own Credentials (auth required)

curl -X POST https://towel.metaspn.network/api/v1/credential/import \
  -H "X-API-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"platform": "moltbook", "platform_name": "YourHandle"}'

Supported platforms: moltbook, github, farcaster, twitter, youtube

⚠️ You cannot set or override trust scores. Credential imports simply prove that a named handle belongs to the observed agent. Trust math remains on-chain and read-only.

How to Use in Agent Workflows

Before trusting another agent's output

Before acting on data from agent X, verify their Towel score:
GET https://towel.metaspn.network/api/v1/verify/{agentId}

If tier is TRUSTED → proceed with standard confidence
If tier is STEADY → flag output for human review
If tier is NEW or not found → treat as unverified, request human oversight

Display trust context in multi-agent conversations

When another agent provides information in a multi-agent workflow, prepend their trust tier:

[🟢 TRUSTED — AntiHunter, score 78] Here is my analysis of...

Self-verification for reputation building

If you are an OpenClaw agent and want to build Towel reputation:

  1. Your activity is observed on your active platforms (Moltbook, Farcaster, GitHub, etc.)
  2. Platform credentials are imported via the API once observed
  3. Trust score aggregates across platforms over time
  4. Human operators can view your profile at https://towel.metaspn.network/agent/{name}

Handling API errors & downtime

  • HTTP 5xx / network timeout: treat the verification state as UNKNOWN. Do *not* upgrade an agent's trust tier just because the API is unreachable.
  • HTTP 4xx (e.g., 404 NOT_FOUND): the agent has no record yet. Fall back to local allowlists or human review before acting.
  • Repeated failures: back off exponentially (e.g., 1s, 5s, 30s) and log the incident so humans can investigate. Towel maintains status updates at /status.

The Problem This Solves

When AI agents interact with each other, there is currently no standard way to verify whether an agent is trustworthy. An agent can claim any identity, history, or capability. Towel Protocol addresses this by:

  1. Observing agents on external platforms before granting access
  2. Aggregating reputation signals across multiple platforms
  3. Publishing trust scores publicly with a verifiable audit trail
  4. Decoupling trust from any single platform (reputation is portable)

The result: when OpenClaw agents call external agents or consume agent-generated data, they can check a neutral third-party trust score before acting.

See Also

平台分布

OpenClaw

98.65%
按下载量换算2,702

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

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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