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Agent Skill · 开发

linkedin-comment-drafter(linkedin 评论起草者)

linkedin-comment-drafter 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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-comment-drafter 是开发类 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,按安装量在开发类的 21,746 个 Skill 里排第 10,578。

总安装 2,164周安装 92GitHub Stars 公开资料未说明下载 758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-comment-drafter(linkedin 评论起草者)
来源仓库:https://github.com/sergebulaev/linkedin-comment-drafter
安装命令:
openclaw skills install linkedin-comment-drafter
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-comment-drafter

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

使用经过验证的 2026 模板从帖子 URL 起草 1-3 个定制的、高参与度的 LinkedIn 评论选项,并在发布前等待用户批准。

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-comment-drafter;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-comment-drafter 怎么安装?

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

linkedin-comment-drafter 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-comment-drafter 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-comment-drafter 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-comment-drafter 用的人多吗?

公开数据是累计安装 2,164 次,近一周安装 92 次,下载 758 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-comment-drafter 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。
  • 需要处理开发类任务、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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
linkedin-comment-drafter

linkedin 评论起草者 · 本页

2,164—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-comment-drafter
description
Draft a high-quality LinkedIn comment on any post from a URL. Use when the user gives a LinkedIn post URL and asks to comment on it. The skill parses the URL, reads the post context, drafts 1-3 comment variants in the user's voice using 2026 hook patterns (first-commenter, data-first, answer-the-closing-question, quotable-reframe), picks a reaction type, and waits for approval before posting via Publora. Keywords: linkedin comment, engage post, comment draft, first commenter, linkedin reply strategy.

LinkedIn Comment Drafter

Produce conversation-provoking comments on any LinkedIn post from a URL. The skill targets the patterns that actually got author replies in 2026 testing (Kevin Payne / Ivan Tsybaev patterns) and avoids the thesis-restatement patterns that die with zero engagement.

When to use

  • User pastes a LinkedIn post URL and says "comment on this", "draft me a comment", "engage with this post"
  • User wants to be among the first 3 commenters on a viral post
  • User wants to reply to a closing question the author asked

Input

A LinkedIn post URL in any of the standard shapes (see the top-level SKILL.md URL table).

Output

1-3 draft comment variants, each with:

  • 200-350 char body, 1-2 short paragraphs, no em dashes, no hashtags
  • Assigned reaction type: LIKE, PRAISE, EMPATHY, INTEREST, APPRECIATION, or ENTERTAINMENT
  • Pattern label (which of the 7 templates was used)
  • Estimated engagement fit based on what the author typically responds to

Then waits for user approval. On "post", calls Publora to react + comment.

Steps

  1. Parse the URL. Use lib.url_parser.parse_linkedin_url to get post_urn and, if present, the post's activity ID.
  2. Fetch the post body. If HarvestAPI is available via corporate-knowledge/personal/knowledge/tools/social_poster/src/harvest_client.py, pull the post text and top 3 existing comments (to avoid duplicate takes). If not, ask the user to paste the post text.
  3. Detect the author's closing question. If the post ends with a "?" line, the Answer-the-Closing-Question template usually wins.
  4. Draft comment variants. Pick 2-3 templates from references/comment-templates.md that fit the post's topic. Fill them with user-voice phrasing.
  5. Run the humanizer pass. Strip em dashes, AI vocab, uniform sentence rhythm. Add a specific number or named entity if missing.
  6. Present drafts for approval using lib.approval.render_approval_card. Include: target URL, each variant, reaction suggestion, a one-line "why this template fits".
  7. On approval — adapt to the active backend. Call lib.active_backend():

- publora (PUBLORA_API_KEY set) → react to the post with the chosen reaction type, pause 8-15s, then post via lib.PubloraClient.create_comment (top-level, no parent_comment). Return the comment URN. - manual (no backend configured — the default) → output the approved draft via lib.manual_mode_message(draft_text, target_url, kind="comment"). This gives the user a copy-paste block plus a one-time setup prompt for Publora (the preferred auto-post path). Do NOT attempt to post programmatically. - diy (LINKEDIN_SKILLS_CUSTOM_POSTER set) → invoke the user's configured custom poster command with the draft text + target URL as arguments.

Templates (see references/comment-templates.md for full list)

  • T1 Missing-Piece (Kevin Payne pattern, highest hit rate): [Name] the [their-thesis] argument misses one piece.. [what-moved]. when [their-condition], the real differentiator is [specific-skill], not [their-focus].
  • T2 Answer-the-Closing-Question: direct answer + one concrete example + why it matters
  • T3 Data-First: half the [population] I see now [behavior]. the [old-assumption] broke around [date]. [new-rule].
  • T4 Practitioner Observation: when X the system does Y, when X' it does Y'. that's when [outcome] kicks in.
  • T5 Counter-with-Concession: agree on point 1, push back on point 2 with one rooted reason
  • T6 Quotable-Reframe: one line under 12 words + expansion
  • T7 Ask-a-Sharper-Question: the harder version of this question is..

Hard rules

  • 200-350 chars. Don't exceed.
  • Always capitalize the author's name (e.g., "Dharmesh", not "dharmesh").
  • No em dashes, no hashtags, no emoji unless the post itself uses them.
  • No mention of the user's own product by name. Describe what they do instead.
  • Never paste generic praise ("Great post!", "This.", "100%"). The skill refuses.
  • Skip the comment if the post is sponsored, a generic listicle, or the author has already deleted it.

Example invocation

User: "Comment on this: https://www.linkedin.com/posts/dharmesh_activity-7448808898326654978-iW20" Skill: [parses URL, fetches post, detects closing question "Seen this in your market?", drafts 3 variants] Skill returns: T2 Answer-the-Closing-Question variant as primary pick, with T1 Missing-Piece as backup, reaction INTEREST, one-line rationale, and approval prompt.

Files in this skill

  • SKILL.md — this file
  • references/comment-templates.md — the 7 templates with fill-in slots and real examples
  • references/voice-rules.md — the specific voice rules from user feedback memories

Related skills

  • linkedin-reply-handler — if you're replying to a comment (not posting top-level)
  • linkedin-humanizer — for aggressive AI-tell scrubbing
  • linkedin-hook-extractor — if you want to use the author's own hook as the basis for your reply

平台分布

OpenClaw

75.64%
按下载量换算573

安全审计

VirusTotal

可疑

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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