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Agent skill

Linkedin Content Repurposer

by borghei in borghei/Claude-Skills

Turns something made for another channel (a thread, a video or talk transcript, a blog post, a newsletter) into a post that reads as native to LinkedIn, without changing what the source says.

MITAuto-check passedWriting & Content

Install Linkedin Content Repurposer

skills CLI
$ npx skills add borghei/Claude-Skills --skill linkedin-content-repurposer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install borghei/Claude-Skills linkedin-content-repurposer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tools/linkedin/linkedin-content-repurposer .claude/skills/linkedin-content-repurposer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
linkedin-content-repurposer
GitHub stars
881
Token cost
~3.6k tokens
SKILL.md length
2,001 words
Files
13 (incl. scripts, references, assets)
Skills in repo
349
Repo updated
First seen
Licence
MIT

At a glance

Turns something made for another channel (a thread, a video or talk transcript, a blog post, a newsletter) into a post that reads as native to LinkedIn, without changing what the source says.

  • Works in 5 steps: Save the source text locally. Do not… → Run the analyser. Read the Move line… → Read every rework finding: each is… → …
  • Existing material should become a LinkedIn post rather than writing one from a blank page
  • SKILL.md covers When to use this skill, Inputs the skill expects, Clarify First and Workflows, plus 3 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Linkedin Content Repurposer is an agent skill from borghei/Claude-Skills. Turns something made for another channel (a thread, a video or talk transcript, a blog post, a newsletter) into a post that reads as native to LinkedIn, without changing what the source says. Use when existing material should become a LinkedIn post rather than writing one from a blank page.

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts, reference files and assets (for example `assets/repurposing_brief_template.md`, `assets/sample_article.md` and `references/fidelity-rules.md`).

It sits in Writing & Content, covering Content repurposing, Social media posts and Blog and article writing. It works with LinkedIn. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Existing material should become a LinkedIn post rather than writing one from a blank page
  • Tasks that involve Content repurposing
  • Tasks that involve Social media posts

Example prompts

  • “Use the linkedin-content-repurposer skill to turn something made for another channel (a thread, a video or talk transcript, a blog post, a…”
  • “/linkedin-content-repurposer”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Save the source text locally. Do not clean it first; the analyser needs to
  2. Run the analyser. Read the Move line (compress, expand, split or
  3. Read every rework finding: each is something to remove or remake.
  4. Choose one spine candidate with the author. The candidates are sentences
  5. Fill assets/repurposing_brief_template.md and confirm it with the author

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Linkedin Content Repurposer loads about 3.6k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 80 tokens; SKILL.md has 2,001 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~80
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 2,001 words, ~3,597 tokens.

Download SKILL.mdSave it as .claude/skills/linkedin-content-repurposer/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.
name
linkedin-content-repurposer
description
Turns something made for another channel (a thread, a video or talk transcript, a blog post, a newsletter) into a post that reads as native to LinkedIn, without changing what the source says. Use when existing material should become a LinkedIn post rather than writing one from a blank page.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
borghei
metadata.category
tools
metadata.domain
linkedin
metadata.updated
2026-10-07
metadata.tags
linkedin, repurposing, content-adaptation, transcripts, fidelity-check

LinkedIn Content Repurposer

The usual way to reuse a piece is to paste it and trim. The result carries its old channel with it: a thread arrives with numbering and a call to repost, a talk arrives with "as you can see on this slide", an article arrives as a summary of five points when a post can hold one. Readers recognise the residue at once and read it as something not written for them.

The opposite failure is quieter and worse. In rebuilding the piece, the rewrite improves on it: a rounder number, a percentage the author never calculated, a neat quotation nobody said. The post now claims something the source does not, under the name of the person who made the source.

This skill does both jobs in order. The agent first measures the source and lists what will not survive the move, then rebuilds from the idea rather than the sentences, then checks the draft against the source so that nothing was added on the way.

Offline only. The skill works from text files the user provides. It does not fetch a URL, download a video, pull a transcript, post, schedule or call any API. If the source lives online, the user pastes or saves the text first.

Scope boundary. This skill adapts material that already exists. Writing a post from a blank page or a draft seed is linkedin-post-writer. Removing machine-sounding phrasing from any draft is linkedin-humanizer; scoring or rewriting the opening line in depth is linkedin-hook-analyzer. When the source has no concrete detail and the author has to supply some, that is linkedin-story-interviewer, whose story bank file this skill can optionally read. Deciding which week the repurposed post runs in is linkedin-content-planner. Comments and replies are linkedin-comment-writer, linkedin-reply-manager and linkedin-thread-tracker; profile copy is linkedin-profile-optimizer; reuse of company material by a team is linkedin-employee-advocacy; reading results afterwards is linkedin-engagement-analytics.

When to use this skill

  • "Turn this thread into a LinkedIn post"
  • A talk, webinar or podcast appearance has a transcript and nothing has been done with it
  • A long article or newsletter issue holds several posts and the author keeps meaning to extract them
  • Something did well elsewhere and the pasted version fell flat here
  • A draft has already been made from a source and needs checking for invented figures or leftover artefacts
  • A team wants a repeatable way to mine one recorded talk for a month of posts

Inputs the skill expects

  • The source as a local .txt or .md file: thread text, transcript, article, talk script or newsletter
  • Confirmation that the user wrote it, or has the right to adapt it, and whose name the post goes under
  • The one reader the post is for and the one thing it should ask of them
  • Whether links in the source should appear in the post at all
  • Optional: a story bank file, to widen the set of figures the author has already confirmed and to enforce never-name and no-go lists
  • Optional: a different length band from the default, if the author has their own

Clarify First

Before analysing or drafting, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • Whose words these are — adapting your own talk is editing; adapting a colleague's, a panel's or an employer's needs permission and attribution, and changes whether the post can be first-person at all.
  • One post or several — a long source usually holds more than one; deciding up front stops the draft becoming a summary of everything.
  • Which single point this post carries — the analyser offers candidates, but the author knows which one they would defend in the comments.
  • What happens to links and to co-speakers' remarks — both are easy to carry over by accident and awkward to remove after publishing.

Stop rule: ask only the two that most change the output. If the user says "just convert it", take the top-ranked spine candidate, produce one post, leave links out of the body, and list those assumptions above the draft.

Workflows

Quick start: save the source as a text file, run Workflow 1, draft from the top spine candidate, then run Workflow 2 before showing anyone the result.

Workflow 1 — Analyse the source before writing anything
  1. Save the source text locally. Do not clean it first; the analyser needs to see the artefacts.
  2. Run the analyser. Read the Move line (compress, expand, split or rebuild in place) and the number of posts the source holds.
  3. Read every rework finding: each is something to remove or remake.
  4. Choose one spine candidate with the author. The candidates are sentences to carry the idea from, not sentences to paste.
  5. Fill assets/repurposing_brief_template.md and confirm it with the author before drafting.
bash
python3 tools/linkedin/linkedin-content-repurposer/scripts/repurpose_analyzer.py \
  --input tools/linkedin/linkedin-content-repurposer/assets/sample_thread.txt
Workflow 2 — Check a draft against its source
  1. Save the draft as a text file beside the source.
  2. Run the fidelity check. A blocker means the draft states a figure or quotation the source does not contain.
  3. Resolve blockers by restoring the source's wording or removing the claim. Never resolve one by editing the source to match.
  4. Clear the rework items: copied sentences, leftover artefacts, an opening that talks about where the material came from. Then work through the checklist in references/native-fit-guide.md.
  5. Validate again with --fail-on blocker and hand the draft to the author only when it exits 0.
bash
python3 tools/linkedin/linkedin-content-repurposer/scripts/draft_fidelity_check.py \
  --source tools/linkedin/linkedin-content-repurposer/assets/sample_thread.txt \
  --draft tools/linkedin/linkedin-content-repurposer/assets/sample_draft.txt \
  --fail-on blocker

The sample draft fails on purpose (exit 1): it changes 12 breakdowns to 9, adds a percentage and invents a quotation. assets/sample_draft_clean.txt is the same material rebuilt properly and passes with no findings.

Workflow 3 — Mine a long source for several posts
  1. Run the analyser on the article or transcript in JSON form.
  2. Read posts_in_source and the units list. Treat each unit as a candidate post with its own single point.
  3. For each unit worth using, write one brief. Do not write a "part 1 of 4" series; each post must stand alone for a reader who sees only that one.
  4. Draft and check each post separately against the full source.
  5. Hand the set to planning so the posts are spread across weeks and pillars instead of published back to back.
bash
python3 tools/linkedin/linkedin-content-repurposer/scripts/repurpose_analyzer.py \
  --input tools/linkedin/linkedin-content-repurposer/assets/sample_article.md \
  --format json

Exit-code contract. Both tools: 0 completed; 1 a finding reached the --fail-on level; 2 a file is missing, unreadable, too short, or (for --story-bank) not a story bank.

Decision frameworks

What the Move line means
MoveWhen the analyser says itWhat to doTag
Rebuild in placeSource already sits inside the length bandKeep the length, remake the opening and the joins[PROVEN] Typical for threads
CompressSource is above the band, one main pointKeep one point, cut the others entirely[RECOMMENDED] Cutting beats summarising
SplitSource is well above the band with several sectionsOne post per point, each self-sufficient[RECOMMENDED]
ExpandSource is below the bandAdd the case, the figure and the stake from the author; do not pad[EXPERIMENTAL] Needs new material, so the story bank or the author must supply it
Show full SKILL.md (835 more words)Show less
What may change and what may not
ElementMay changeMust not change
OpeningEntirely rewrittenThe claim it leads to
OrderFreely; lead with the outcome if that is strongerCause and effect
LengthCompressed or expandedWhich facts are stated
SentencesRewritten in the author's written voiceMeaning
FiguresRounded only if the author approves and says soValues, units, periods, what they count
QuotationsTurned into reported speechWording inside quotation marks
People namedRemoved or anonymisedAdded
Length and opening defaults

The band of 800 to 1,600 characters and the 200-character opening window are house heuristics, set as defaults so the tools have something to measure against. They are not platform limits. Post length limits and where the feed truncates a post are current as of writing only; verify them in the product, and override with --target-min, --target-max and --opening-chars.

SourceUsual starting point
ThreadAlready near the band; the work is joins and the opening
Talk transcriptFar above; pick one argument from one section
ArticleAbove; split by section, never summarise
Newsletter issueOne item from it, not the issue
Short note or captionBelow; expand only with the author's own detail

Anti-Patterns

Paste and trim

Mistake: The thread is pasted, the numbering deleted, and the last two segments cut to fit. Why it happens: The source already performed somewhere, so changing it feels like risk, and trimming is quick. Instead: Pick the spine, close the source, and write the post from the idea. The fidelity check reports FD-003 when more than half the draft's sentences are verbatim, which is the signature of trimming.

Summarising the whole piece

Mistake: A forty-minute talk becomes "five things I covered at the conference". Why it happens: Every section cost effort to prepare and leaving any out feels like waste. Instead: One post, one point. The other four are four more posts. The analyser's posts_in_source and RP-023 exist to make this visible before drafting.

Improving the numbers

Mistake: "12 breakdowns, down from 31" becomes "a 61% reduction", or 12 quietly becomes 9. Why it happens: Percentages sound more authoritative, and small slips enter when a rewrite works from memory of the source. Instead: Carry figures exactly, with their units and periods. A derived figure needs the author's sign-off because they will be the one asked to defend it. FD-001 blocks any number the source does not contain.

Tidying a quotation

Mistake: A remark from the transcript is shortened and sharpened, then left in quotation marks. Why it happens: Spoken sentences are messy and the cleaned version is what the speaker "meant". Instead: Either quote the words as spoken or drop the quotation marks and report it. FD-002 blocks quoted passages that do not appear in the source.

Narrating the post's history

Mistake: "I gave a talk last month and wanted to share the key takeaway here." Why it happens: It feels honest to say where the material came from, and it is an easy first line. Instead: Open on the point. Readers care what you found, not which room you found it in. RP-011 and FD-006 flag this.

Speaking for the panel

Mistake: A co-speaker's best line from a panel transcript appears in the first person in the post. Why it happens: Transcripts flatten speakers together, especially once labels are stripped. Instead: Strip nobody's label until you know whose words each passage is. Use only the author's own remarks; credit anything else by name with consent, or leave it out.

Files

Tools overview and reference documentation for this skill:

FilePurpose
scripts/repurpose_analyzer.pyMeasures a source text, detects its channel, lists the artefacts that will not survive the move, recommends compress, expand, split or rebuild, ranks spine candidates and estimates how many posts the source holds
scripts/draft_fidelity_check.pyGate that compares a draft with its source: blocks on new figures and altered quotations, flags copied sentences, leftover artefacts, stale openings and length; optionally reads a story bank
scripts/repurpose_rules.pyRule data and text primitives shared by both tools: the rule catalogue, artefact patterns, sentence splitting, figure extraction; --list-rules prints the catalogue
references/source-format-playbooks.mdPer-channel playbooks: thread, talk and video transcript, article, newsletter, short note; what to keep, cut and rebuild in each
references/native-fit-guide.mdWhat makes a post read as written for LinkedIn: opening, shape, rhythm, ask, links, with platform mechanics marked as verify-in-product
references/fidelity-rules.mdThe contract between source and draft: figures, quotations, attribution, permission, other people's words, and how the gate enforces each
assets/sample_thread.txtNine-part fictional thread with numbering, a handle, a link, a repost ask and a hashtag cluster
assets/sample_talk_transcript.txtFictional talk transcript with timestamps, speaker labels, filler and slide references
assets/sample_article.mdFictional four-section article with headings, a table, a footnote and an image, long enough to split
assets/sample_draft.txtDraft made from the thread by paste and trim, with a changed figure and an invented quotation; fails the gate
assets/sample_draft_clean.txtThe same thread rebuilt properly; passes the gate
assets/repurposing_brief_template.mdFill-in brief agreed with the author before drafting: source, rights, point, reader, ask, carry-over list, cut list

© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 12 other files (scripts, references, assets) in tools/linkedin/linkedin-content-repurposer of borghei/Claude-Skills.

  • SKILL.md
  • assets/repurposing_brief_template.md
  • assets/sample_article.md
  • assets/sample_draft.txt
  • assets/sample_draft_clean.txt
  • assets/sample_talk_transcript.txt
  • assets/sample_thread.txt
  • references/fidelity-rules.md
  • references/native-fit-guide.md
  • references/source-format-playbooks.md
  • scripts/draft_fidelity_check.py
  • scripts/repurpose_analyzer.py
  • scripts/repurpose_rules.py

Open the folder on GitHubat commit 4a698e8

Compare with similar skills

Linkedin Content Repurposer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Linkedin Content Repurposer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Linkedin Content Repurposer this skillborghei/Claude-Skills881—~3.6kAutomated safety check: PassMIT
Li RepurposeJakeschincariol/linkedin-agent-skill1.5k—~680Automated safety check: PassMIT
Content Repurposermohitagw15856/pm-claude-skills1.4k—~1.4kAutomated safety check: PassMIT
Content Repurposerinfometa/workbuddyskills344—~2.2kAutomated safety check: PassNone
Blog RepurposeInfrasity-Labs/dev-gtm-claude-skills139—~2.3kAutomated safety check: PassMIT
Changelog Social RecapFlorianBruniaux/claude-code-ultimate-guide6.1k—~1.8kAutomated safety check: NotesCC-BY-SA-4.0

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Works with

Categories

Questions about Linkedin Content Repurposer

What does Linkedin Content Repurposer do?

Turns something made for another channel (a thread, a video or talk transcript, a blog post, a newsletter) into a post that reads as native to LinkedIn, without changing what the source says. Linkedin Content Repurposer is an agent skill from borghei/Claude-Skills. Turns something made for another channel (a thread, a video or talk transcript, a blog post, a newsletter) into a post that reads as native to LinkedIn, without changing what the source says.

When should I use Linkedin Content Repurposer?

Linkedin Content Repurposer fits situations like: existing material should become a LinkedIn post rather than writing one from a blank page; tasks that involve Content repurposing; tasks that involve Social media posts.

How do I install Linkedin Content Repurposer in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill linkedin-content-repurposer -a claude-code`. Or copy the skill folder (tools/linkedin/linkedin-content-repurposer in borghei/Claude-Skills) into .claude/skills/linkedin-content-repurposer in your project. Claude Code loads it when a task matches its description.

How do I install Linkedin Content Repurposer in Codex?

Run `npx skills add borghei/Claude-Skills --skill linkedin-content-repurposer -a codex`. Or copy the skill folder (tools/linkedin/linkedin-content-repurposer in borghei/Claude-Skills) into .agents/skills/linkedin-content-repurposer in your project. Codex loads it when a task matches its description.

Can I use Linkedin Content Repurposer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill linkedin-content-repurposer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkedin-content-repurposer, .gemini/skills/linkedin-content-repurposer, .github/skills/linkedin-content-repurposer and .opencode/skills/linkedin-content-repurposer in your project.

What does Linkedin Content Repurposer need to run?

Going by SKILL.md and its folder, Linkedin Content Repurposer needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Linkedin Content Repurposer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Linkedin Content Repurposer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Linkedin Content Repurposer use?

Linkedin Content Repurposer is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Linkedin Content Repurposer use?

About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.2k tokens, read only when the agent opens those files.

What are the alternatives to Linkedin Content Repurposer?

Skills that share tags, products or a category with Linkedin Content Repurposer: Li Repurpose (Jakeschincariol/linkedin-agent-skill, 1.5k stars), Content Repurposer (mohitagw15856/pm-claude-skills, 1.4k stars), Content Repurposer (infometa/workbuddyskills, 344 stars) and Blog Repurpose (Infrasity-Labs/dev-gtm-claude-skills, 139 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linkedin Content Repurposer?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 881 GitHub stars. The repository holds 349 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.