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Agent Skill · 研究检索

x-tag-responder(x 标签响应器)

x-tag-responder 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。

x-tag-responder 是研究检索类 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,按安装量在研究检索类的 73,675 个 Skill 里排第 33,756。

总安装 2,305周安装 98GitHub Stars 公开资料未说明下载 808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:x-tag-responder(x 标签响应器)
来源仓库:https://github.com/m-lwatcher/x-tag-responder
安装命令:
openclaw skills install x-tag-responder
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 x-tag-responder

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。

x-tag-responder 用于检测他人线程中对 AI 的标记行为,并生成恰当回应方案。适用于维护 AI 人设、优化人机交互体验或提升社交回应质量的任务。可获取完整对话上下文,推断用户意图并制定符合语境的回复建议。

安装命令为 openclaw skills install x-tag-responder,需接入 X API 获取实时通知流。使用前应评估响应延迟与内容审核机制,确保输出符合平台规范与伦理要求。

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 x-tag-responder;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

x-tag-responder 怎么安装?

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

x-tag-responder 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。

x-tag-responder 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。

x-tag-responder 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。

x-tag-responder 用的人多吗?

公开数据是累计安装 2,305 次,近一周安装 98 次,下载 808 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。

x-tag-responder 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。
  • 需要处理研究检索类任务、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。

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
x-tag-responder

x 标签响应器 · 本页

2,305—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
x-tag-responder
description
Detects when a human tags their AI familiar in someone else's X/Twitter thread, fetches full conversation context, infers intent, and crafts an appropriate reply. Handles X API reply-chain restrictions gracefully.
metadata

X Tag Responder — Skill Reference

This skill activates when your human tags you (their AI familiar) in someone else's X/Twitter thread. It fetches the full conversation, infers their intent, drafts a fitting reply, and handles X API reply-chain restrictions.


Prerequisites

  • xurl CLI installed at /home/linuxbrew/.linuxbrew/bin/xurl (or on PATH as xurl)
  • Config at ~/.xurl with valid OAuth1 or OAuth2 credentials
  • Never read, print, or expose ~/.xurl contents to the LLM context

Trigger Patterns

This skill is relevant when the user says things like:

  • "I tagged you in a tweet / thread"
  • "Check out this tweet I tagged you in"
  • "Weigh in on this" (with a tweet URL or ID)
  • "Reply to this for me" (with context)
  • They paste a tweet URL or ID and imply the agent should respond

Step-by-Step Workflow

Step 1 — Identify the Tagged Tweet

Extract the tweet ID or URL from the user's message. It will look like:

  • https://x.com/username/status/1234567890
  • https://twitter.com/username/status/1234567890
  • A bare numeric ID like 1234567890

If unclear, ask the user: *"What's the tweet URL or ID you tagged me in?"*


Step 2 — Fetch the Tagged Tweet

Read the tweet the human tagged you in:

xurl read TWEET_ID

This returns full tweet data including: text, author_id, conversation_id, in_reply_to_user_id, referenced_tweets.

Note the conversation_id — it identifies the root of the thread.


Step 3 — Fetch Thread / Conversation Context

Pull the broader conversation using the conversation_id from Step 2:

xurl search "conversation_id:CONVERSATION_ID" -n 20

This retrieves recent tweets in the thread. Sort mentally by id (ascending = chronological).

Build a mental model of:

  • Who started the thread and what they said
  • What the thread is about (topic, tone, stance)
  • Where the tagged tweet sits in the conversation
  • What the human's tagged tweet says (their cue to you)

Step 4 — Infer Human Intent

Read what the human wrote when they tagged you. Infer one of these intents:

Cue in tag tweetLikely intent
"What do you think?" / "Thoughts?"Weigh in with a take
"Reply to this" / "Handle this"Draft a reply on their behalf
"Is this true?" / "Fact-check"Research and report back (don't post)
"lol check this out"Just read/acknowledge, probably no reply needed
No cue text — just a tagAsk the human what they want
"@agent check the math"Analyze/verify, reply if appropriate

When uncertain, default to: draft a reply and ask the human to approve before posting.


Step 5 — Draft the Reply

Craft a reply that:

  • Matches the tone of the thread (technical → precise; casual → relaxed; debate → grounded)
  • Stays concise (X has a 280-char limit; aim under 240 to leave room for context)
  • Speaks as the agent or for the human — whichever the intent implies
  • Does not start with "I" (Twitter convention + feels robotic)
  • Does not use hollow filler like "Great point!" unless it's sarcastic and earned

Present the draft to the human for review before posting:

*"Here's a draft reply. Should I post it?* [DRAFT TEXT]"

Step 6 — Post the Reply (with Human Approval)

Once the human approves:

xurl reply TWEET_ID "Your reply text here"

Where TWEET_ID is the ID of the specific tweet you are replying to (usually the tweet the human tagged you in, or the thread root if instructed).


⚠️ X API Reply-Chain Restriction

The X API only allows you to reply to a tweet if your account is mentioned somewhere in the reply chain.

This means:

  • If the thread is between two other users and you are not already in it, xurl reply will fail with a 403 or silently not thread correctly.
  • The tagged tweet (where your human mentioned you) creates your entry point — you CAN reply to that tweet.
  • You cannot reply to arbitrary tweets in the thread that don't mention you.

Handling the Restriction

If reply succeeds: Report back with the posted tweet URL.

If reply fails (403 / authorization error / "not allowed"):

Report back clearly:

"I can't reply directly to that tweet — I'm not in the reply chain. Here's what I'd say though: [DRAFT TEXT] Options: 1. Tag me directly in the specific tweet you want me to reply to — that adds me to the chain. 2. You post the reply yourself and I'll write it for you. 3. I can quote-tweet instead (no chain restriction): just confirm."

Offering a quote-tweet fallback:

xurl quote TWEET_ID "Your reply text here"

Quote-tweets bypass the reply-chain restriction entirely.


Error Reference

ErrorMeaningFix
403 ForbiddenNot in reply chainReport + suggest re-tag or quote-tweet
401 UnauthorizedAuth expiredRun xurl auth status; re-auth if needed
429 Too Many RequestsRate limitedWait ~15 min and retry
Tweet not foundDeleted or privateTell the human the tweet is inaccessible

Full Example Session

Human says:

"I tagged you in this tweet — weigh in: https://x.com/someuser/status/9876543210"

Agent workflow:

# 1. Read the tagged tweet
xurl read 9876543210
# → Note: conversation_id=1111111111, text="@quirk what do you think of this?", author=human

# 2. Fetch thread context
xurl search "conversation_id:1111111111" -n 20
# → Read thread: original author debating AI regulation, 5 replies

# 3. Infer intent: "What do you think?" → weigh in

# 4. Draft reply (280 chars max):
# "Regulation works best when it's targeted at outcomes, not methods.
#  Banning specific architectures is a game of whack-a-mole — 
#  but liability frameworks? That actually scales. 🧵"

# 5. Present to human for approval

# 6. Post if approved:
xurl reply 9876543210 "Regulation works best when it's targeted at outcomes, not methods. Banning specific architectures is whack-a-mole — but liability frameworks scale. 🧵"

Tips

  • Read before you write. Always fetch the full thread before drafting. Context is everything on X.
  • Match the register. A shitpost thread and a policy debate are not the same. Sound like you belong.
  • Short > long. Twitter threads reward punchy. If you need more space, thread it.
  • Always confirm before posting. Unless the human explicitly says "just post it," show the draft first.
  • Quote-tweet is always available. When in doubt, quote-tweet bypasses all chain restrictions.

Security Notes

  • Never print or expose ~/.xurl — it contains API keys and tokens.
  • Never use --verbose / -v in agent sessions — can expose auth headers.
  • Always confirm with the human before posting publicly on their behalf.
  • Credentials are handled by xurl internally; do not pass tokens as CLI flags in agent context.

平台分布

OpenClaw

91.32%
按下载量换算738

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

可疑

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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