Content

Content → LinkedIn Posts

Turn any content the user shares into 3-4 finished LinkedIn posts, ready to publish.

Setup note: This skill pairs with the post skill, which carries the user's voice profile. Make sure both are installed. References below assume both skills live under your skills directory (e.g. ~/.claude/skills/post/SKILL.md and ~/.claude/skills/factcheck/SKILL.md) — adjust the paths if yours are different.

Step 1: Get the Content

Identify what the user has provided and handle accordingly:

Pasted text or notes — use directly from the conversation.

PDF or uploaded file — read the pdf-reading skill (if available) for extraction instructions before proceeding.

URL or web page — use web_fetch to retrieve the full page content.

Email — search Gmail using relevant terms from the user's description. Fetch the full thread.

Newsletter — if the user has a recurring newsletter they pull from, search Gmail for the sender address and fetch the most recent edition. Extract plain text body; ignore tracking pixels, unsubscribe links, and HTML artifacts.

Nothing provided — ask the user what content they'd like to repurpose, or default to whatever recurring source you've been set up to use.

Step 2: Identify the Best 3-4 Angles

Read through the content and find the strongest raw material across these four angles. Not every piece will have all four equally — pick the best 3-4 total, don't force weak ones.

• Hot take / opinion — A claim or framing the user could stake a strong position on. Something that pushes back on conventional wisdom.
• Surprising stat or data point — A number that would stop someone mid-scroll and reframe how they think about a topic.
• Practical tip — A tool, framework, or piece of advice someone could apply immediately.
• Story or narrative — A real moment, case, or observation that opens a post in a human way.

Step 3: Draft the Posts

Critical rule: use the user's exact words wherever possible if they wrote the source (newsletter, email, notes). Lift sentences, transitions, and analogies directly — don't paraphrase their phrasing into something blander. If the source is third-party (a PDF, article, URL), extract the core ideas and write in the user's voice using the post skill.

For each post:

• Open with the sharpest, most concrete line available — not a setup, not a broad statement
• Do not open with newsletter meta-framing ("This week's newsletter covers..." / "I wrote about this on the plane...")
• Stay inside the insight — the post should stand alone without any reference to the newsletter
• Use the voice profile from the post skill (read its SKILL.md before drafting)

Write full, un-hatcheted drafts first. Paragraph form. Do not pre-trim.

Step 4: Run /factcheck on Any Posts with Stats

Before presenting, identify any posts containing statistics, named figures, or specific claims attributed to organizations or surveys. Run the factcheck skill on those posts (standard tier).

Read the factcheck SKILL.md and verify all checkable claims via web search.

Apply any corrections directly into the drafts before presenting. Note what was fixed and why — one line per fix, after the posts.

Step 5: Present the Posts

Present all posts in full, ready to copy-paste. Label each with its angle type.

After the posts, include a single short note on any factcheck fixes applied.

Ask the user which (if any) they want to adjust, shorten, or take in a different direction.

What NOT to do

• Do not open any post with a reference to the source ("This week's newsletter...", "I read a PDF that...", "In this report...")
• Do not paraphrase the user's phrasing into generic language — use their words when they wrote the source
• Do not run hatchet automatically — only shorten if asked
• Do not present post ideas before drafts — go straight to finished posts