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Agent Skill · 研究检索

linkedin-reply-handler(linkedin 回复处理程序)

linkedin-reply-handler 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。

linkedin-reply-handler 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 34,331。

总安装 2,235周安装 96GitHub Stars 公开资料未说明下载 783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:linkedin-reply-handler(linkedin 回复处理程序)
来源仓库:https://github.com/sergebulaev/linkedin-reply-handler
安装命令:
openclaw skills install linkedin-reply-handler
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 linkedin-reply-handler

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。

从给定的评论 URL 起草精确的 LinkedIn 评论回复,处理线程结构以在正确的顶级评论 URN 下发布。

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 linkedin-reply-handler;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

linkedin-reply-handler 怎么安装?

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

linkedin-reply-handler 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。

linkedin-reply-handler 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。

linkedin-reply-handler 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。

linkedin-reply-handler 用的人多吗?

公开数据是累计安装 2,235 次,近一周安装 96 次,下载 783 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。

linkedin-reply-handler 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
linkedin-reply-handler

linkedin 回复处理程序 · 本页

2,235—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
linkedin-reply-handler
description
Draft a reply to any existing LinkedIn comment from a URL. Use when the user wants to reply to a comment on someone else's post, reply to a reply on their own post, or follow up in a thread where the author just responded. The skill parses the commentUrn from the URL, figures out the correct parentComment target (LinkedIn flattens threads to 2 levels), drafts the reply in the user's voice, and waits for approval before posting via Publora. Keywords: linkedin reply, reply to comment, thread continuation, comment URL, parent comment URN.

LinkedIn Reply Handler

Drafts a reply to a specific LinkedIn comment. Correctly handles LinkedIn's 2-level thread flattening: if you're replying to a reply, the Publora API needs the TOP-level comment URN as parentComment, not the reply's URN.

When to use

  • User pastes a LinkedIn comment URL (contains ?commentUrn=...) and says "reply to this"
  • An author (e.g., Kevin Payne, Felix Tseitlin) replied to the user's comment and the user wants to continue the thread
  • User wants to re-engage a conversation that's gone dormant

Input

A LinkedIn URL containing commentUrn=urn:li:comment:(activity:POST,COMMENT_ID) — either the direct comment permalink or a feed URL with the query fragment.

Output

  • 1-2 reply drafts, 150-300 chars each
  • Reaction suggestion for the comment being replied to (always react before replying)
  • Thread context summary (who said what, when)
  • Approval card → on user "post", fires reaction + reply via Publora

Steps

  1. Parse the URL. lib.url_parser.parse_linkedin_url returns post_urn, comment_id, comment_urn.
  2. Determine thread structure. Fetch the post's comment thread (HarvestAPI if available) and locate the comment. Figure out whether it's:

- a top-level comment (parentComment = this comment's URN when replying) - a reply to a top-level comment (parentComment = the TOP comment's URN, not this reply's URN — LinkedIn flattens)

  1. Read the full context. Author post text, top-level comment text, any intermediate replies. Include the user's own prior comment if they're in the thread.
  2. Draft the reply. Follow the engagement templates in references/reply-templates.md. If the counterpart asked a question, answer it directly. If they pushed back, concede then sharpen.
  3. Humanizer pass. Strip em dashes, AI vocab, enforce varied sentence length.
  4. Approval card. Include thread preview (who said what in last 3 turns), the draft, reaction suggestion, and the parentComment URN we'll send.
  5. On approval — adapt to the active backend. Call lib.active_backend():

- publora (PUBLORA_API_KEY set) → react on the specific comment being replied to, pause 8-15s, then post reply with the correct top-level parentComment URN. - manual (no backend configured — the default) → output the approved reply via lib.manual_mode_message(draft_text, target_url, kind="reply"). Include the parent comment URL so the user knows exactly where to paste. Do NOT attempt to post. - diy (LINKEDIN_SKILLS_CUSTOM_POSTER set) → invoke the custom poster with draft, target URL, and parent-comment URN.

The flattening gotcha

LinkedIn only nests replies two levels deep. Visually the thread looks like:

Top comment by Alice (id: 111)
└─ Reply by Bob (id: 222)          ← parentComment: urn:li:comment:(activity:POST, 111)
   └─ Reply by Carol (id: 333)     ← parentComment: STILL urn:li:comment:(activity:POST, 111)

Carol's reply doesn't nest under Bob's — it's pinned at level 2 to the same top comment. If you pass urn:li:comment:(activity:POST, 222) as parentComment, the API returns 400 on some paths or silently misplaces the reply.

Rule in this skill: always use the TOP-level comment's URN as parentComment. If you're replying to a 2nd-level reply, we walk up the tree to find the top comment.

Templates (references/reply-templates.md)

  • R1 Answer-Their-Question — they asked, you answer plainly + one real detail
  • R2 Concede-Then-Sharpen — "you're right on X, and the piece I'd push on is Y"
  • R3 Extend-Their-Thesis — take their point one layer deeper with a new framing
  • R4 Share-Lived-Experience — "we hit this last quarter — here's what broke"
  • R5 Ask-Back — redirect with a sharper question when their position needs more context

Hard rules

  • 150-300 chars. Replies are tighter than top-level comments.
  • React to the comment you're replying to, not to the parent post.
  • Capitalize the counterpart's first name.
  • Never paste a canned "thanks!" — either respond with content or don't reply.
  • If the thread is older than 72 hours, consider a DM instead (use linkedin-thread-engagement).

Example

User: "Reply to this: https://www.linkedin.com/feed/update/urn:li:activity:7449018753880834048?commentUrn=urn%3Ali%3Acomment%3A%28activity%3A7449018753880834048%2C7449758545140453376%29" Skill: parses → post 7449018753880834048, comment 7449758545140453376. Fetches thread. Sees: Kevin Payne's post → Serge's comment ("moat moved to taste") → Kevin's reply ("How are you building that conviction muscle with your team?"). Drafts R1 Answer-Their-Question variant. Shows approval card. User: "post" Skill: react APPRECIATION on Kevin's reply → pause 12s → post reply with parentComment set to Serge's original comment URN (the TOP level, not Kevin's reply).

Files

  • SKILL.md — this file
  • references/reply-templates.md — 5 reply templates with examples
  • references/threading-rules.md — LinkedIn's 2-level flattening explained with edge cases

平台分布

OpenClaw

77.24%
按下载量换算605

安全审计

VirusTotal

通过

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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