Crawler Summary

qq-auto-reply answer-first brief

QQ 桌面端自动回复技能(macOS)。通过 AppleScript + 截图实现 QQ 消息读取和自动回复。支持激活 QQ、截取聊天窗口、搜索联系人、发送消息。agent 通过截图分析消息内容,然后调用 reply 命令发送回复。 --- name: qq-auto-reply description: QQ 桌面端自动回复技能(macOS)。通过 AppleScript + 截图实现 QQ 消息读取和自动回复。支持激活 QQ、截取聊天窗口、搜索联系人、发送消息。agent 通过截图分析消息内容,然后调用 reply 命令发送回复。 --- QQ 自动回复技能(macOS) 通过 AppleScript + screencapture 自动化 macOS QQ 桌面端,实现消息读取和自动回复。 使用场景 - 用户需要自动回复 QQ 消息时 - 用户需要批量发送 QQ 消息时 - 用户需要监控 QQ 聊天记录时 前置条件 1. macOS 系统,已安装 QQ 桌面版(/Applications/QQ.app) 2. QQ 已登录 3. 系统偏好设置中已授予终端/IDE **辅助功能权限**(System Preferences → Privacy & Sec Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

Freshness

Last checked 4/14/2026

Best For

qq-auto-reply is best for general automation workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 94/100

qq-auto-reply

QQ 桌面端自动回复技能(macOS)。通过 AppleScript + 截图实现 QQ 消息读取和自动回复。支持激活 QQ、截取聊天窗口、搜索联系人、发送消息。agent 通过截图分析消息内容,然后调用 reply 命令发送回复。 --- name: qq-auto-reply description: QQ 桌面端自动回复技能(macOS)。通过 AppleScript + 截图实现 QQ 消息读取和自动回复。支持激活 QQ、截取聊天窗口、搜索联系人、发送消息。agent 通过截图分析消息内容,然后调用 reply 命令发送回复。 --- QQ 自动回复技能(macOS) 通过 AppleScript + screencapture 自动化 macOS QQ 桌面端,实现消息读取和自动回复。 使用场景 - 用户需要自动回复 QQ 消息时 - 用户需要批量发送 QQ 消息时 - 用户需要监控 QQ 聊天记录时 前置条件 1. macOS 系统,已安装 QQ 桌面版(/Applications/QQ.app) 2. QQ 已登录 3. 系统偏好设置中已授予终端/IDE **辅助功能权限**(System Preferences → Privacy & Sec

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Apr 14, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 14, 2026

Vendor

Wszrw123

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

Setup snapshot

git clone https://github.com/wszrw123/qq-auto-reply.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Wszrw123

profilemedium
Observed Apr 14, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 14, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

6

Snippets

0

Languages

typescript

Parameters

Executable Examples

bash

python3 qq_auto.py open

bash

# 截取当前聊天窗口
python3 qq_auto.py read

# 截取会话列表
python3 qq_auto.py list

bash

python3 qq_auto.py search --name "联系人名称"

bash

# 发送消息
python3 qq_auto.py reply --message "你好!"

# 试运行(只输入不发送)
python3 qq_auto.py reply --message "测试内容" --dry-run

bash

# 监听所有消息,自动回复
python3 qq_auto.py monitor -r "稍等,马上回复你"

# 只监听 find! 的消息,10秒后回复
python3 qq_auto.py monitor -t "find!" -r "收到,稍后回复" --delay 10

# 只回复一次
python3 qq_auto.py monitor --max-replies 1 -r "在忙,稍后回复"

# 仅记录事件不回复(供 agent 处理)
python3 qq_auto.py monitor

text

qq-auto-reply/
├── SKILL.md          # 本文件
├── qq_auto.py        # 核心自动化脚本
├── screenshots/      # 截图存放目录
└── logs/             # 操作日志 + 发送记录

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

QQ 桌面端自动回复技能(macOS)。通过 AppleScript + 截图实现 QQ 消息读取和自动回复。支持激活 QQ、截取聊天窗口、搜索联系人、发送消息。agent 通过截图分析消息内容,然后调用 reply 命令发送回复。 --- name: qq-auto-reply description: QQ 桌面端自动回复技能(macOS)。通过 AppleScript + 截图实现 QQ 消息读取和自动回复。支持激活 QQ、截取聊天窗口、搜索联系人、发送消息。agent 通过截图分析消息内容,然后调用 reply 命令发送回复。 --- QQ 自动回复技能(macOS) 通过 AppleScript + screencapture 自动化 macOS QQ 桌面端,实现消息读取和自动回复。 使用场景 - 用户需要自动回复 QQ 消息时 - 用户需要批量发送 QQ 消息时 - 用户需要监控 QQ 聊天记录时 前置条件 1. macOS 系统,已安装 QQ 桌面版(/Applications/QQ.app) 2. QQ 已登录 3. 系统偏好设置中已授予终端/IDE **辅助功能权限**(System Preferences → Privacy & Sec

Full README

name: qq-auto-reply description: QQ 桌面端自动回复技能(macOS)。通过 AppleScript + 截图实现 QQ 消息读取和自动回复。支持激活 QQ、截取聊天窗口、搜索联系人、发送消息。agent 通过截图分析消息内容,然后调用 reply 命令发送回复。

QQ 自动回复技能(macOS)

通过 AppleScript + screencapture 自动化 macOS QQ 桌面端,实现消息读取和自动回复。

使用场景

  • 用户需要自动回复 QQ 消息时
  • 用户需要批量发送 QQ 消息时
  • 用户需要监控 QQ 聊天记录时

前置条件

  1. macOS 系统,已安装 QQ 桌面版(/Applications/QQ.app
  2. QQ 已登录
  3. 系统偏好设置中已授予终端/IDE 辅助功能权限(System Preferences → Privacy & Security → Accessibility)
  4. Python 依赖:pip install pyautogui pillow

工作流程

第一步:激活 QQ

python3 qq_auto.py open

第二步:读取消息(截图)

# 截取当前聊天窗口
python3 qq_auto.py read

# 截取会话列表
python3 qq_auto.py list

截图保存在 screenshots/ 目录,agent 通过查看截图分析消息内容。

第三步:搜索联系人(可选)

python3 qq_auto.py search --name "联系人名称"

第四步:发送回复

# 发送消息
python3 qq_auto.py reply --message "你好!"

# 试运行(只输入不发送)
python3 qq_auto.py reply --message "测试内容" --dry-run

命令参考

| 命令 | 说明 | |------|------| | open | 启动/激活 QQ 窗口 | | read | 截取当前 QQ 聊天窗口截图 | | list | 截取 QQ 会话列表截图 | | search --name <名称> | 搜索联系人/群聊并打开对话 | | reply --message <内容> | 在当前聊天窗口发送消息 | | reply --message <内容> --dry-run | 只输入不发送(测试用) | | monitor -r <回复内容> | 监听新消息并自动回复 | | monitor -t <联系人> -r <回复内容> | 仅监听指定联系人 |

monitor 参数

| 参数 | 说明 | 默认值 | |------|------|--------| | --target, -t | 仅监听指定联系人(包含匹配) | 所有联系人 | | --auto-reply, -r | 自动回复内容,不指定则仅记录事件 | 无 | | --delay | 回复延迟秒数 | 15 | | --jitter | 延迟随机抖动范围±秒 | 5 | | --poll | 轮询间隔秒数 | 5 | | --max-replies | 最大回复次数,0=无限 | 0 | | --dry-run | 只输入不发送 | false |

监听示例

# 监听所有消息,自动回复
python3 qq_auto.py monitor -r "稍等,马上回复你"

# 只监听 find! 的消息,10秒后回复
python3 qq_auto.py monitor -t "find!" -r "收到,稍后回复" --delay 10

# 只回复一次
python3 qq_auto.py monitor --max-replies 1 -r "在忙,稍后回复"

# 仅记录事件不回复(供 agent 处理)
python3 qq_auto.py monitor

检测机制

  1. 窗口监控:每5秒检查 QQ 窗口列表,新聊天窗口出现 = 有人找你
  2. Dock 徽章:监控 QQ Dock 图标未读徽章数变化

回复延迟建议

  • 默认 15秒 ± 5秒随机抖动(实际10~20秒),自然不显机器人
  • 快速回复:--delay 5 --jitter 2(3~7秒)
  • 慢速回复:--delay 30 --jitter 10(20~40秒)

Agent 使用示例

当用户说"帮我回复 QQ 消息"时,agent 应:

  1. python3 qq_auto.py open — 激活 QQ
  2. python3 qq_auto.py read — 截取聊天窗口
  3. 查看截图,分析对方发送的消息内容
  4. 根据上下文组织回复内容
  5. python3 qq_auto.py reply --message "回复内容" — 发送回复

当用户说"帮我给张三发 QQ 消息"时:

  1. python3 qq_auto.py open — 激活 QQ
  2. python3 qq_auto.py search --name "张三" — 搜索并打开对话
  3. python3 qq_auto.py reply --message "消息内容" — 发送消息

目录结构

qq-auto-reply/
├── SKILL.md          # 本文件
├── qq_auto.py        # 核心自动化脚本
├── screenshots/      # 截图存放目录
└── logs/             # 操作日志 + 发送记录

注意事项

  1. 辅助功能权限:首次使用需在系统设置中授予辅助功能权限,否则 AppleScript 无法控制 QQ
  2. 中文输入:通过剪贴板粘贴实现,会覆盖当前剪贴板内容
  3. 窗口焦点:发送消息前会自动激活 QQ 窗口,确保 QQ 不在最小化状态
  4. 安全:建议先用 --dry-run 测试,确认无误后再实际发送
  5. QQ 版本:适配 macOS QQ 桌面版,不支持 QQ NT 网页版

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/snapshot"
curl -s "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/contract"
curl -s "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 5d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-16T23:41:28.468Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Wszrw123",
    "href": "https://github.com/wszrw123/qq-auto-reply",
    "sourceUrl": "https://github.com/wszrw123/qq-auto-reply",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-14T22:24:05.132Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-14T22:24:05.132Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/wszrw123-qq-auto-reply/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Sponsored

Ads related to qq-auto-reply and adjacent AI workflows.