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Agent Skill · 研究检索

noizai-chat-with-anyone(noizai 与任何人聊天)

noizai-chat-with-anyone 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

noizai-chat-with-anyone 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;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 73,674 个 Skill 里排第 13,273。

总安装 9,523周安装 389GitHub Stars 公开资料未说明下载 3,081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
0.1.1

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:noizai-chat-with-anyone(noizai 与任何人聊天)
来源仓库:https://github.com/ksuriuri/noizai-chat-with-anyone
安装命令:
openclaw skills install noizai-chat-with-anyone
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 noizai-chat-with-anyone

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。

通过自动在线查找任何真实的人或虚构人物的语音,提取干净的参考样本,并以他们自己的声音与任何真实的人或虚构人物聊天。

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 noizai-chat-with-anyone;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

    它需要接触敏感数据,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

noizai-chat-with-anyone 怎么安装?

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

noizai-chat-with-anyone 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。

noizai-chat-with-anyone 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

noizai-chat-with-anyone 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。

noizai-chat-with-anyone 用的人多吗?

公开数据是累计安装 9,523 次,近一周安装 389 次,下载 3,081 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。

noizai-chat-with-anyone 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
noizai-chat-with-anyone

noizai 与任何人聊天 · 本页

9,523—接触敏感数据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
chat-with-anyone
description
Chat with any real person or fictional character in their own voice by automatically finding their speech online, extracting a clean reference sample, and generating audio replies. Also supports generating a matching voice from an uploaded image. Use when the user says "我想跟xxx聊天", "你来扮演xxx跟我说话", "让xxx给我讲讲这篇文章", "我想跟图片中的人说话", or similar.
permissions
metadata
{"openclaw": {"primaryEnv": "NOIZ_API_KEY"}}

Chat with Anyone

Clone a real person's voice from online video, or design a voice from a photo, then roleplay as that person with TTS.

Important: Ethical Use & Copyright

This skill synthesizes speech that imitates real voices. Before proceeding, the agent must:

  1. Never impersonate someone to deceive, defraud, or harass.
  2. Only use publicly available media (public speeches, interviews, press conferences) as reference audio.
  3. Inform the user that generated audio is synthetic and should not be presented as genuine recordings.
  4. Decline requests that target private individuals who have not consented, or that are clearly intended for deception, harassment, or defamation.

If the user's intent appears harmful, refuse politely and explain why.

Prerequisites

DependencyTypeHow to verify
ffmpegSystem binaryffmpeg -version
yt-dlpSystem binaryyt-dlp --version
tts skillCursor skillls skills/tts/scripts/tts.py
NOIZ_API_KEYEnv var or filepython3 skills/tts/scripts/tts.py config --show

Before the first run, verify all dependencies are present:

ffmpeg -version && yt-dlp --version && ls skills/tts/scripts/tts.py

If yt-dlp is missing, install it:

uv pip install yt-dlp

If the Noiz API key is not configured:

python3 skills/tts/scripts/tts.py config --set-api-key YOUR_KEY

Mode Selection

  • User names a person (real or fictional) --> Workflow A
  • User provides an image, person is unrecognizable --> Workflow B
  • User provides an image, person is a recognizable public figure --> Workflow A (real voice is more authentic)
  • Multiple people in image --> Ask which person first

Workflow A: Name-based (voice from online video)

Track progress with this checklist:

- [ ] A1. Disambiguate character
- [ ] A2. Find reference video
- [ ] A3. Download audio + subtitles
- [ ] A4. Extract best reference segment
- [ ] A5. Generate speech

A1. Disambiguate Character

If ambiguous (e.g. "US President", "Spider-Man actor"), ask the user to specify the exact person before proceeding.

A2. Find a Reference Video

Use web search to find a YouTube (or Bilibili) video of the person speaking clearly. Best candidates: interviews, speeches, press conferences. Avoid videos with heavy background music.

Search queries to try:

  • {CHARACTER_NAME} interview / {CHARACTER_NAME} 采访
  • {CHARACTER_NAME} speech / {CHARACTER_NAME} 演讲
  • {CHARACTER_NAME} press conference

A3. Download Audio and Subtitles

mkdir -p "tmp/chat_with_anyone/{CHARACTER_NAME}"
yt-dlp -x --audio-format mp3 \
  --write-subs --write-auto-subs --sub-langs "en,zh-Hans" \
  --convert-subs srt \
  -o "tmp/chat_with_anyone/{CHARACTER_NAME}/%(title)s.%(ext)s" \
  "{VIDEO_URL}"

After download, list the output directory to identify the audio file and SRT subtitle file:

ls tmp/chat_with_anyone/{CHARACTER_NAME}/

Expected output: a .mp3 audio file and one or more .srt subtitle files.

If no subtitle files appear: try a different video that has auto-generated captions, or adjust --sub-langs for the target language.

A4. Extract Best Reference Segment

Use the automated extraction script — it parses the SRT, finds the densest 3-12 second speech window, and extracts it as a WAV:

python3 skills/chat-with-anyone/scripts/extract_ref_segment.py \
  --srt "tmp/chat_with_anyone/{CHARACTER_NAME}/{SRT_FILE}" \
  --audio "tmp/chat_with_anyone/{CHARACTER_NAME}/{AUDIO_FILE}" \
  -o "tmp/chat_with_anyone/{CHARACTER_NAME}/ref.wav"

The script prints the selected time range and saves the reference WAV. Verify the output exists and is non-empty before proceeding.

If the script reports no suitable segment: try --min-duration 2 for shorter clips, or download a different video.

A5. Generate Speech and Roleplay

Write a response in character, then synthesize it:

python3 skills/tts/scripts/tts.py \
  -t "{RESPONSE_TEXT}" \
  --ref-audio "tmp/chat_with_anyone/{CHARACTER_NAME}/ref.wav" \
  -o "tmp/chat_with_anyone/{CHARACTER_NAME}/reply.wav"

Present the generated audio file to the user along with the text. For subsequent messages, reuse the same --ref-audio path.


Workflow B: Image-based (voice from photo)

Track progress with this checklist:

- [ ] B1. Analyze image
- [ ] B2. Design voice
- [ ] B3. Preview (optional)
- [ ] B4. Generate speech

B1. Analyze the Image

Use your vision capability to examine the image:

  1. If the person is a recognizable public figure --> switch to Workflow A for authentic voice.
  2. If unrecognizable, produce a voice description covering:

- Gender (male / female) - Approximate age (e.g. "around 30 years old") - Apparent demeanor (e.g. cheerful, authoritative, gentle) - Contextual cues (e.g. suit --> professional tone; athletic outfit --> energetic)

B2. Design the Voice

Pass both the image and the description to the voice-design script:

python3 skills/chat-with-anyone/scripts/voice_design.py \
  --picture "{IMAGE_PATH}" \
  --voice-description "{VOICE_DESCRIPTION}" \
  -o "tmp/chat_with_anyone/voice_design"

The script outputs:

  • Detected voice features (printed to stdout)
  • Preview audio files in the output directory
  • voice_id.txt containing the best voice ID

Read the voice ID:

cat tmp/chat_with_anyone/voice_design/voice_id.txt

B3. Preview (Optional)

Present the preview audio files from the output directory so the user can hear the voice. If unsatisfied, re-run B2 with adjusted --voice-description or --guidance-scale.

B4. Generate Speech and Roleplay

python3 skills/tts/scripts/tts.py \
  -t "{RESPONSE_TEXT}" \
  --voice-id "{VOICE_ID}" \
  -o "tmp/chat_with_anyone/voice_design/reply.wav"

For subsequent messages, keep using the same --voice-id for consistency.


Example: Name-based

User: 我想跟特朗普聊天,让他给我讲个睡前故事。

Agent steps:

  1. Character: Donald Trump. No disambiguation needed.
  2. Search Donald Trump speech youtube, find a clear speech video.
  3. Download:

yt-dlp -x --audio-format mp3 --write-subs --write-auto-subs --sub-langs "en" --convert-subs srt -o "tmp/chat_with_anyone/trump/%(title)s.%(ext)s" "https://youtube.com/watch?v=..."

  1. Extract reference:

python3 skills/chat-with-anyone/scripts/extract_ref_segment.py --srt "tmp/chat_with_anyone/trump/....srt" --audio "tmp/chat_with_anyone/trump/....mp3" -o "tmp/chat_with_anyone/trump/ref.wav"

  1. Generate TTS in Trump's style:

python3 skills/tts/scripts/tts.py -t "Let me tell you a tremendous bedtime story..." --ref-audio "tmp/chat_with_anyone/trump/ref.wav" -o "tmp/chat_with_anyone/trump/reply.wav"

  1. Present reply.wav and the story text to the user.

Example: Image-based

User: [uploads photo.jpg] 我想跟这张图片里的人聊天

Agent steps:

  1. Vision analysis: unrecognizable young woman, ~25, casual sweater, warm smile.
  2. Design voice:

python3 skills/chat-with-anyone/scripts/voice_design.py --picture "photo.jpg" --voice-description "A young Chinese woman around 25, gentle and warm voice, friendly tone" -o "tmp/chat_with_anyone/voice_design"

  1. Read voice ID from tmp/chat_with_anyone/voice_design/voice_id.txt.
  2. Generate TTS:

python3 skills/tts/scripts/tts.py -t "你好呀!很高兴认识你!" --voice-id "{VOICE_ID}" -o "tmp/chat_with_anyone/voice_design/reply.wav"

  1. Present audio and continue roleplay with same --voice-id.

Troubleshooting

ProblemSolution
yt-dlp download fails or video unavailableTry a different video URL; some regions/videos are restricted. Run yt-dlp -U to update
No SRT subtitle filesRe-download with --sub-lang en,zh-Hans; if still none, try a different video with auto-captions
extract_ref_segment.py finds no suitable windowUse --min-duration 2 for shorter clips, or try a different video
Voice design returns errorCheck Noiz API key; ensure image is a clear photo of a person
TTS output sounds wrongFor Workflow A, try a different reference video; for Workflow B, adjust --voice-description

平台分布

OpenClaw

78.49%
按下载量换算2,418

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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