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linkedin-thread-engagementlinkedin 线程参与度

Agent Skill

linkedin-thread-engagement 用于辅助安全审计、权限检查和凭据风险排查,适合在 OpenClaw 中需要复核安全边界、认证流程或敏感配置时使用。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。

总安装

2,225

周安装

90

GitHub Stars

公开资料未说明

下载量

698
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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-thread-engagement(linkedin 线程参与度)
来源仓库:https://github.com/sergebulaev/linkedin-thread-engagement
安装命令:
openclaw skills install linkedin-thread-engagement
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-thread-engagement

简介

跟踪您在 LinkedIn 上的评论,以便作者在 72 小时内回复,标记高价值的参与窗口,并起草及时的后续行动,以最大限度地提高帖子动力。

SKILL.md

name
linkedin-thread-engagement
description
Monitor LinkedIn threads where the user commented for author replies and inbound signals. Use when the user wants to track which of their comments earned personal replies from post authors (the highest-value engagement signal). Flags the 6-24h "Kevin Payne window" where author replies are most likely, drafts follow-up responses, and optionally routes to DM. Keywords: thread monitoring, author reply, inbound tracking, comment follow-up, engagement compound.

LinkedIn Thread Engagement

The engagement compounding layer. Tracks which of the user's comments earned author replies, drafts timely follow-ups, and flags the 6-24 hour window where thread momentum is highest.

When to use

  • Daily: "What threads need follow-up today?"
  • After posting a batch of comments: "Check back in 6 hours"
  • When an author replied personally (e.g., Kevin Payne → Serge): "Draft the response"

Input

  • User's LinkedIn profile URL (to pull their recent comments)
  • Optional: specific post URL to monitor

Output

Daily report

PostedAuthorPostCommentReply?StageAction
18h agoKevin PayneLawVu"moat moved to taste"✅ Kevin replied 14h agoWarm (6-24h window)Reply now
22h agoDharmesh ShahHubSpot"integration depth moat"NoColdSkip
3h agoFelix T.Rezolve"twin economies"NoWatchCheck in 3h

For each warm thread

  • Thread preview (last 3 turns)
  • Suggested response (drafted via linkedin-reply-handler)
  • Reaction target (the specific reply URN, not the post)
  • Priority (high / medium / low)

Weekly roll-up

  • Total comments posted
  • Author-reply rate (target: 15%+)
  • Conversion to DM (when thread closes warm)

Steps

  1. Fetch user's recent comments via HarvestAPI /linkedin/profile-comments.
  2. For each comment posted in last 72h: fetch the parent post's comment tree and look for:

- Replies to the user's comment - Whether the author posted any of those replies - Timestamps (time since user's comment, time since latest reply)

  1. Classify stage:

- Hot (<6h): author just replied — respond within 90 min for max thread momentum - Warm (6-24h): the Kevin Payne window — author replies most happen here - Cool (24-72h): still respondable but lower velocity - Dormant (>72h): don't reply in thread; consider DM

  1. Draft responses for warm threads using linkedin-reply-handler (which adapts to the active backend per lib.active_backend() — Publora auto-posts, manual mode returns copy-paste, DIY invokes custom poster).
  2. Flag suspicious patterns:

- Author replied but also deleted someone else's comment (author is actively moderating, tread carefully) - Commenter is in thread self-promoting (your reply shouldn't engage them)

  1. DM routing: if thread is dormant but the author engaged meaningfully, draft a DM that references the thread specifically.

Kevin Payne window

Named after the real 2026-04 data point: Kevin Payne (LawVu CEO) replied to Serge's comment 22h after the original post. This is the sweet spot.

  • 0-6h: 70% of author replies happen here if they're going to happen
  • 6-24h: ~25% of author replies, but these are higher-quality (author took time to think)
  • >24h: thread rarely produces new author engagement

Follow-up timing:

  • If author replied in 0-6h window: respond within 90 minutes
  • If author replied in 6-24h window: respond within 2 hours (they're still checking)
  • If author replied >24h: respond within 4 hours before thread goes cold

Inbound-quality signals

High-quality commenter = worth the follow-up:

  • Founder/operator title in profile
  • Company in user's ICP
  • Active posting history (not just reactions)
  • Mutual 2nd-degree connections >10
  • Prior thoughtful comments on user's posts

Low-quality = skip:

  • Generic praise with no specifics
  • Template language ("I'd love to hop on a quick call")
  • Profile is sales/agency with no operator history
  • Same comment across many creators' posts

Hard rules

  • Never reply to a reply later than 72h after the thread's last turn. Switch to DM.
  • Never chain 3+ replies under one comment (thread spam).
  • If the author deleted their reply, do not reply — they reconsidered.
  • Don't DM a warm thread before first replying publicly (skips a step).

Example

Input: monitor sbulaev profile, last 24h
Output: - 1 warm thread: Kevin Payne replied 14h ago on LawVu post. Current stage: Warm (8-24h). Suggested response ready. Action: post within 2 hours. - 8 cold threads (no author engagement). Skip. - 3 watching threads (<6h old, author may still reply). Check again in 3-6h.

Files

  • SKILL.md — this file
  • references/thread-timing.md — the timing matrix with examples

Related skills

  • linkedin-reply-handler — drafts the actual follow-up message
  • linkedin-comment-drafter — drafts the initial comment that starts threads

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.56%
按下载量换算583

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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