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)

2. Audience (e.g. recruiters, engineers, designers, founders, managers, students).

3. Tone (default: "professional but friendly"):

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

4. Length:

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

5. Language (default: English unless user text suggests another).

6. 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.

2. 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.

3. 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.

4. 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.

5. 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".

6. 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").

2. 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.

3. 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.