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linkedin-post-generator-nivaslinkedin 帖子生成器 Nivas

Agent Skill

linkedin-post-generator-nivas 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。

总安装

2,596

周安装

104

GitHub Stars

1

下载量

840
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-post-generator-nivas(linkedin 帖子生成器 Nivas)
来源仓库:https://github.com/ksrinivas2304/linkedin-post-generator-nivas
安装命令:
openclaw skills install linkedin-post-generator-nivas
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-post-generator-nivas

简介

根据简短提示或大纲在本地生成高质量的 LinkedIn 帖子。

  • 适用于快速起草、重写或优化 LinkedIn 内容。
  • 输入主题、关键词或草稿,返回结构化文案建议。
  • 输出结果需经人工校验,确保事实准确与表达得体。
  • 适合日常维护人设与定期发布专业动态时使用。linkedin-post-generator-nivas 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
linkedin-post-generator
description
Generate high-quality LinkedIn posts locally from a short prompt, topic, or outline. Use when the user asks to draft, rewrite, or improve a LinkedIn post, headline, or caption, including adding hooks, CTAs, or tailoring tone and length.

LinkedIn Post Generator

This skill helps generate and refine LinkedIn posts locally on this machine, without calling the LinkedIn API. The user will copy-paste the final post into LinkedIn manually.

When to use this skill

Use this skill whenever the user asks for help with:

  • Writing a new LinkedIn post from a topic, idea, or outline
  • Rewriting or improving an existing LinkedIn post
  • Adjusting tone (professional, casual, storytelling, technical, etc.)
  • Changing length (short, medium, long / thread-style)
  • Adding hooks, CTAs, or hashtags suitable for LinkedIn

Examples of triggering requests:

  • "Draft a LinkedIn post about my new project in AI"
  • "Rewrite this LinkedIn post to be more engaging"
  • "Make this post more professional and concise for LinkedIn"
  • "Give me 3 hook options for this LinkedIn update"

Srinivas-specific optimization

When the user is Kusumanchi Srinivas (headline mentions SRKR CSE ’25 / Associate ML Engineer @Yanthraa / Research Associate @Li2 Edu):

  • Optimize posts for:

- Growing reach, followers, likes, comments, and impressions on a professional audience. - Attracting engineers, founders, recruiters, tech leaders, and ambitious students across software and AI.

  • Emphasize themes that fit his profile and past posts, without locking into a tiny niche:

- Software engineering and backend/system design. - AI/ML and data-driven products. - Cloud and modern infrastructure when relevant. - Career growth, mindset, and lessons from internships, research, and real projects. - Tech leadership, teamwork, and how to think about building products.

  • Avoid:

- Over-focusing on old “B.Tech student” identity (keep it light if used at all). - Internal project names, sprint labels, file names, or code snippets unless explicitly requested.

Inputs to collect

When the user asks for a LinkedIn post, try to clarify these (only ask follow-ups if not obvious):

  1. Goal of the post (choose or infer):

- announce (launch, promotion, new role, milestone) - share learning (lesson, story, failure, insight) - ask (help, feedback, hiring, referrals) - promote (product, service, content)

  1. Audience (e.g. recruiters, engineers, designers, founders, managers, students).
  1. Tone (default: "professional but friendly"):

- options: professional, friendly, casual, storytelling, technical, inspirational.

  1. Length:

- short (1–3 paragraphs) - medium (3–6 paragraphs) - long (story/essay-style)

  1. Language (default: English unless user text suggests another).
  1. Input content:

- either a topic/outline, or an existing draft to improve.

If the user is being very casual ("just write something"), use sensible defaults and do not over-question.

Workflow

Follow this workflow:

  1. Parse the request

- Identify if the user provided: topic only, topic + key points, or a full draft. - Infer goal, audience, tone, and length when obvious.

  1. Clarify if needed

- Ask at most 1–3 short follow-up questions when critical details are missing. - Skip questions if the request is clear enough to produce something useful.

  1. Generate a first draft

- Use the scripts/generate_post.py helper when available. - If script output is missing or script is unavailable, generate directly in the model.

  1. Polish for LinkedIn conventions

Ensure the post generally follows these patterns (adapt when user asks otherwise):

- Strong first line (hook) that makes people stop scrolling. - Short paragraphs (1–3 lines) and some line breaks for readability. - Clear structure: hook → context/story → insight/value → CTA (optional). - Avoid heavy emoji spam; 0–3 emojis max unless user wants more. - Optional light hashtags at the end (2–6), relevant and non-spammy.

  1. Offer variants when helpful

- By default, provide 1 main post. - Optionally add: - 2–3 alternative hooks, or - a shorter / more concise variant, when that seems useful or the user asks for "options".

  1. Respect user constraints

- If the user gives a word/character limit, target within ~10–15%. - Keep or adapt any mandatory phrases, links, or hashtags they specify.

Helper script: scripts/generate_post.py

If this repository includes scripts/generate_post.py, prefer calling it for deterministic formatting.

Expected behavior (conceptual):

  • Input (arguments or stdin JSON):

- topic / prompt - optional: audience, tone, length, language, and any raw draft text

  • Output: a single LinkedIn-ready post on stdout (no extra explanations).

If the script is missing or fails, fall back to generating the post directly in this agent.

Style guidelines

When generating LinkedIn posts, always optimize for reach and engagement on a professional audience, not internal team context.

  • Audience-first: Assume the reader does *not* know the project, sprint names, or internal file names. Explain in plain language.
  • Voice: Clear, confident, and human. Avoid corporate buzzword soup.
  • Jargon: Use domain terms only when audience would understand them.
  • Specifics over vagueness: Prefer concrete, relatable examples and outcomes ("faster app, smoother experience") over internal details ("Sprint 2, PHASE3_RUNTIME_INTERACTION.md").
  • Brevity: Say what matters in as few words as needed; avoid filler.
  • Authenticity: When user shares personal story, preserve their voice and details.
  • No raw code or private data: Never paste code, logs, or internal data into the post unless the user explicitly says it’s a code-focused audience.
  • Hook for attention: Prioritize strong first lines that make professionals stop scrolling.

Safety & compliance

  • Do not fabricate employment history, degrees, or certifications unless explicitly requested as a fictional/sample post.
  • Avoid discriminatory, harassing, or misleading content.
  • If the user asks for unethical growth-hacking (spammy DMs, fake testimonials, deceptive claims), gently refuse and suggest ethical alternatives.

Example usages

  1. New post from topic
User: "Write a LinkedIn post announcing I joined ACME as a Senior Data Engineer in Bangalore, excited about building real-time pipelines. Keep it professional and a bit warm."

Action:

  • Infer goal: announce new role
  • Audience: professional network, recruiters, colleagues
  • Tone: professional but warm
  • Length: short/medium
  • Generate a post with a clear hook and a brief CTA (e.g. "If you work in data infra, would love to connect").
  1. Rewrite a draft
User: "Make this more engaging for LinkedIn while keeping the main points: [user draft]"

Action:

  • Keep all factual claims.
  • Improve hook, structure, and flow.
  • Preserve any required links or hashtags.
  1. Multiple hooks
User: "Give me 5 hook ideas for a LinkedIn post about switching careers from mechanical engineering to data science."

Action:

  • Produce 5 strong first-line hook options tailored to LinkedIn.

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

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

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

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按下载量换算644

安全审计

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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

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