whatsapp-ultimate

SKILLAI 工具
AI 工具 未标注权限 许可证不明确
安装这个技能

You put 5 agents in a WhatsApp group. They all respond at once. Your API bill does a backflip. Protocol v2 fixes that — congestion control, conversation lifecycle, and budget-aware scheduling. Agents that know when to talk, when to shut up, and when to burn unused tokens before reset. Built for the TinkerClaw fork — github.com/globalcaos/tinkerclaw.

一句话选型结论

按资料字段整理

whatsapp-ultimate是AI 工具类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类AI 工具 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
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权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_15292d5a/yjkj-whatsapp-ultimate
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

AI 工具
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_15292d5a仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791673997
正文体量13.8 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
组合多个 AI 能力

把写作、检索、总结串成一条流程。

搭工作流

把固定流程做成可重复调用的步骤。

做提示词与评测

整理提示词并对比输出效果。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在AI 工具场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
whatsapp-ultimate当前 未标注权限 未标注 未标注 未标注 有
执行计划 只读 GitHub 仓库 151.5 万 Codex、Claude、Cursor 有
Playwright MCP 测试 浏览器控制 ClawHub 市场 136.5 万 OpenClaw 有
完成前的验证 未标注权限 GitHub 仓库 131.9 万 Codex、Claude、Cursor 有
子 Agent 驱动开发 只读 GitHub 仓库 131.2 万 Codex、Claude、Cursor 有
前端设计 执行命令 GitHub 仓库 125.6 万 Codex、Claude、Cursor 有

SKILL.md 全文

13.8 KB
模型实际读到的说明书原文,来自技能仓库

TinkerClaw WhatsApp

> Part of TinkerClaw — our OpenClaw fork running 24/7 with real-time token tracking, self-improving crons, and persistent cognitive memory.

<scope>
Everything you can do in WhatsApp, your AI agent can do too. This skill documents all WhatsApp capabilities available through OpenClaw's native channel integration. No external Docker services, no CLI wrappers — direct WhatsApp Web protocol via Baileys.
</scope>


<prerequisites>
- OpenClaw with WhatsApp channel configured
- WhatsApp account linked via QR code (openclaw whatsapp login)
</prerequisites>


Capabilities Overview

Category Features
Messaging Text, media, polls, stickers, voice notes, GIFs
Interactions Reactions, replies/quotes, edit, unsend
Groups Create, rename, icon, description, participants, admin, invite links
History Full-text search, vCard contact extraction with phone numbers

Total: 22 distinct actions.


Messaging

Send Text

message action=send channel=whatsapp to=&quot;+34612345678&quot; message=&quot;Hello!&quot;

Send Media (Image/Video/Document)

message action=send channel=whatsapp to=&quot;+34612345678&quot; message=&quot;Check this out&quot; filePath=/path/to/image.jpg

Supported: JPG, PNG, GIF, MP4, PDF, DOC, etc.

Send Poll

message action=poll channel=whatsapp to=&quot;+34612345678&quot; pollQuestion=&quot;What time?&quot; pollOption=[&quot;3pm&quot;, &quot;4pm&quot;, &quot;5pm&quot;]

Send Sticker

message action=sticker channel=whatsapp to=&quot;+34612345678&quot; filePath=/path/to/sticker.webp

Must be WebP format, ideally 512x512.

Send Voice Note

message action=send channel=whatsapp to=&quot;+34612345678&quot; filePath=/path/to/audio.ogg asVoice=true

Use OGG/Opus format for voice notes — MP3 may not play correctly.

Send GIF

message action=send channel=whatsapp to=&quot;+34612345678&quot; filePath=/path/to/animation.mp4 gifPlayback=true

Convert GIF to MP4 first (WhatsApp requires this):

ffmpeg -i input.gif -movflags faststart -pix_fmt yuv420p -vf &quot;scale=trunc(iw/2)*2:trunc(ih/2)*2&quot; output.mp4 -y

Interactions

Add Reaction

message action=react channel=whatsapp chatJid=&quot;34612345678@s.whatsapp.net&quot; messageId=&quot;ABC123&quot; emoji=&quot;🚀&quot;

Remove Reaction

message action=react channel=whatsapp chatJid=&quot;34612345678@s.whatsapp.net&quot; messageId=&quot;ABC123&quot; remove=true

Reply/Quote Message

message action=reply channel=whatsapp to=&quot;34612345678@s.whatsapp.net&quot; replyTo=&quot;QUOTED_MSG_ID&quot; message=&quot;Replying to this!&quot;

Edit Message (Own Messages Only)

message action=edit channel=whatsapp chatJid=&quot;34612345678@s.whatsapp.net&quot; messageId=&quot;ABC123&quot; message=&quot;Updated text&quot;

Unsend/Delete Message

message action=unsend channel=whatsapp chatJid=&quot;34612345678@s.whatsapp.net&quot; messageId=&quot;ABC123&quot;

Group Management

Create Group

message action=group-create channel=whatsapp name=&quot;Project Team&quot; participants=[&quot;+34612345678&quot;, &quot;+34687654321&quot;]

Rename Group

message action=renameGroup channel=whatsapp groupId=&quot;123456789@g.us&quot; name=&quot;New Name&quot;

Set Group Icon

message action=setGroupIcon channel=whatsapp groupId=&quot;123456789@g.us&quot; filePath=/path/to/icon.jpg

Set Group Description

message action=setGroupDescription channel=whatsapp groupJid=&quot;123456789@g.us&quot; description=&quot;Team chat for Q1 project&quot;

Add Participant

message action=addParticipant channel=whatsapp groupId=&quot;123456789@g.us&quot; participant=&quot;+34612345678&quot;

Remove Participant

message action=removeParticipant channel=whatsapp groupId=&quot;123456789@g.us&quot; participant=&quot;+34612345678&quot;

Promote to Admin

message action=promoteParticipant channel=whatsapp groupJid=&quot;123456789@g.us&quot; participants=[&quot;+34612345678&quot;]

Demote from Admin

message action=demoteParticipant channel=whatsapp groupJid=&quot;123456789@g.us&quot; participants=[&quot;+34612345678&quot;]

Leave Group

message action=leaveGroup channel=whatsapp groupId=&quot;123456789@g.us&quot;

Get Invite Link

message action=getInviteCode channel=whatsapp groupJid=&quot;123456789@g.us&quot;

Returns: https://chat.whatsapp.com/XXXXX

Revoke Invite Link

message action=revokeInviteCode channel=whatsapp groupJid=&quot;123456789@g.us&quot;

Get Group Info

message action=getGroupInfo channel=whatsapp groupJid=&quot;123456789@g.us&quot;

Returns: name, description, participants, admins, creation date.


JID Formats

WhatsApp uses JIDs (Jabber IDs) internally:

Type Format Example
Individual &lt;number&gt;@s.whatsapp.net 34612345678@s.whatsapp.net
Group &lt;id&gt;@g.us 123456789012345678@g.us

When using to= with phone numbers, OpenClaw auto-converts to JID format.


Tips

Voice Notes

Use OGG/Opus format:

ffmpeg -i input.wav -c:a libopus -b:a 64k output.ogg

Stickers

Convert images to WebP stickers:

ffmpeg -i input.png -vf &quot;scale=512:512:force_original_aspect_ratio=decrease,pad=512:512:(ow-iw)/2:(oh-ih)/2:color=0x00000000&quot; output.webp

Rate Limits

WhatsApp has anti-spam measures. Avoid:
- Bulk messaging to many contacts
- Rapid-fire messages
- Messages to contacts who haven't messaged you first

Message IDs

To react/edit/unsend, you need the message ID. Incoming messages include this in the event payload. For your own sent messages, the send response includes the ID.


Comparison with Other Skills

Feature whatsapp-ultimate wacli whatsapp-automation gif-whatsapp
Native integration yes no (CLI) no (Docker) N/A
Send text yes yes no no
Send media yes yes no no
Polls yes no no no
Stickers yes no no no
Voice notes yes no no no
GIFs yes no no yes
Reactions yes no no no
Reply/Quote yes no no no
Edit yes no no no
Unsend yes no no no
Group create yes no no no
Group management yes (full) no no no
Receive messages yes yes yes no
Two-way chat yes no no no
External deps None Go binary Docker + WAHA ffmpeg


Protocol v2: Multi-Agent Discussions

<why_this_matters>
If you put multiple AI agents in one WhatsApp group, the naive default is everyone responds to everything. Five agents replying to one message means 5x the API spend per turn, plus echo loops where agents agree with each other forever. Protocol v2 introduces congestion control, conversation lifecycle, and budget-aware scheduling so agents know when to talk, when to stay quiet, and when to wrap up.
</why_this_matters>

Agent Identity

Each agent gets its own personality, icon, and (optionally) model:

channels:
  whatsapp:
    agentIcon: &quot;🤖&quot;          # single-agent icon prefix
    turnEndMarker: &quot;⚡&quot;       # end-of-turn marker in 1:1 chats
    multiAgent:
      mainAgentId: &quot;jarvis&quot;
      agents:
        jarvis:
          id: &quot;jarvis&quot;
          name: &quot;Jarvis&quot;
          icon: &quot;🤖&quot;
        luna:
          id: &quot;luna&quot;
          name: &quot;Luna&quot;
          icon: &quot;🌙&quot;
          model: &quot;sonnet&quot;
        rex:
          id: &quot;rex&quot;
          name: &quot;Rex&quot;
          icon: &quot;🦖&quot;
          model: &quot;haiku&quot;

Agent personalities live in the workspace:

workspace/
├── SOUL.md                  # main agent
├── agents/
│   ├── luna/SOUL.md         # Luna&#x27;s personality
│   └── rex/SOUL.md          # Rex&#x27;s personality

Intra-Agent Chats

Register WhatsApp groups where agents discuss freely (no trigger prefix needed):

      intraAgentChats:
        brainstorm:
          chatId: &quot;120363424201898007@g.us&quot;
          participants: [&quot;jarvis&quot;, &quot;luna&quot;, &quot;rex&quot;]
          owner: &quot;oscar&quot;
          mode: &quot;broadcast&quot;        # broadcast | addressed | round-robin

Routing modes:
- broadcast — all agents respond (with congestion control)
- addressed — only respond when mentioned by name ("Luna, what do you think?")
- round-robin — structured turn-taking

Congestion Control (Exponential Courtesy Protocol)

Prevents N agents from all responding simultaneously:

      congestion:
        enabled: true
        baseDelayFactor: 150     # ms × agentCount² base delay
        maxDelay: 30000          # 30s cap
        backpressureThreshold: 1.5  # slow down over-talkers
        windowMs: 60000          # 60s sliding window

How it works:
- Base delay scales quadratically with agent count (2 agents ≈ 600ms, 5 agents ≈ 3750ms)
- Random jitter prevents synchronization
- Agents talking more than their fair share get 2× delay penalty
- If another agent posts during your wait, restart the timer (yield-on-collision)

Conversation Lifecycle

Agents detect when discussions go stale and know when to wrap up:

      lifecycle:
        stalenessWindow: 5        # compare last N messages
        stalenessThreshold: 0.85  # cosine similarity trigger
        maxTurnsPerObjective: 30  # hard cap
        autoClose: true

Features:
- Staleness detection — cosine similarity of message embeddings detects circular discussions
- Agreement loop detection — catches "I agree" / "Good point" / "Exactly" loops
- Topic steering — one agent claims pivot role to redirect conversation
- Objective tracking — set goals, track completion, auto-close with summary
- Closure protocol — propose → ack → converge (all agents must agree)

Budget-Aware Scheduling

Adjusts conversation depth based on API usage and reset timing:

      budget:
        provider: &quot;anthropic&quot;
        windowDays: 7
        burnModeEnabled: true
        burnTriggerHours: 24     # hours before reset
        burnUsageThreshold: 0.20 # usage below 20%

Four modes:

Mode When Congestion Staleness Max Turns Tangents
Conservative >85% used 2× slower 0.80 ½ No
Moderate 60-85% Normal 0.85 Normal No
Aggressive <60% 0.7× faster 0.85 Normal Yes
Burn <20% used, <24h to reset 0.3× faster 0.95 2× Encouraged

Burn mode philosophy: unused tokens expire at reset. Better to have emergent agent-agent discussions than waste the budget.

DM Trigger Prefix

Protocol v2 extends triggerPrefix to DMs (previously groups only):

  • Owner — always bypasses triggerPrefix
  • Authorized contacts — must start message with prefix (e.g., "Jarvis, help me with...")
  • Intra-agent chats — bypass triggerPrefix entirely

Turn-End Marker

In 1:1 chats (selfChat or owner-only DM), append a visual marker to signal turn completion:

channels:
  whatsapp:
    turnEndMarker: &quot;⚡&quot;

4.0.0

  • Protocol v2: Multi-agent discussions with configurable routing (broadcast/addressed/round-robin)
  • Added: Congestion control — Exponential Courtesy Protocol prevents message explosion in multi-agent chats
  • Added: Conversation lifecycle — staleness detection, agreement loop detection, topic steering, objective tracking, closure protocol
  • Added: Budget-aware scheduling — four spending modes including burn mode for pre-reset token usage
  • Added: Agent identity system — per-agent SOUL.md, icons, names, model overrides
  • Added: DM triggerPrefix gating — non-owner contacts must use prefix in DMs
  • Added: Turn-end marker (⚡) for 1:1 chats
  • Added: agentIcon config for outbound message prefixing

3.7.0

  • Added: vCard phone number extraction — contact messages now return structured vcard field with names and phone numbers
  • Added: contactsArrayMessage support — multi-contact shares are now parsed
  • Improved: New contact messages store phone numbers in text_content for full-text search (e.g. search by phone number)
  • Improved: raw_json now included in search results for contact-type messages, enabling vCard extraction from historical data

3.4.0

  • Fixed: Chat search now resolves LID/JID aliases — searching by chat name finds messages across both @lid and @s.whatsapp.net JID formats
  • Added: resolveChatJids() cross-references chats, contacts, and messages tables to discover all JID aliases for a given chat filter
  • Improved: Search falls back to original LIKE behaviour if no JIDs resolve, so no regressions

3.0.0

Your Agent
    ↓
OpenClaw message tool
    ↓
WhatsApp Channel Plugin
    ↓
Baileys (WhatsApp Web Protocol)
    ↓
WhatsApp Servers

No external services. No Docker. No CLI tools. Direct protocol integration.


Pairs Well With

  • smart-model-router — auto-select the right model per agent role (creative → Sonnet, analyst → Haiku, devil's advocate → GPT)
  • agent-superpowers — verification iron law and three-agent review for when your multi-agent discussions produce code
  • subagent-overseer — monitor agent sessions without burning tokens on polling loops

https://github.com/globalcaos/tinkerclaw

Clone it. Fork it. Break it. Make it yours.


License

MIT — Part of OpenClaw


Links

  • OpenClaw: https://github.com/openclaw/openclaw
  • Baileys: https://github.com/WhiskeySockets/Baileys
  • ClawHub: https://clawhub.com

常见问题

5 问
答案由本站依据条目字段整理
whatsapp-ultimate怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_15292d5a/yjkj-whatsapp-ultimate。安装方式为未标注。装完刷新技能列表或重开客户端。

whatsapp-ultimate支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

whatsapp-ultimate权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

whatsapp-ultimate收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

whatsapp-ultimate用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。