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).

2. 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).

2. 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.