What is linkedin-repurposer?

An agent that rewrites existing material for LinkedIn, a professional networking platform, while adapting its story, tone, and business focus.

Use it to extract business lessons, shape professional stories, present expertise naturally, and create content intended to encourage meaningful engagement on LinkedIn.

It helps turn general or longer source material into posts suited to professional readers and LinkedIn discussions.

How WomenDefiningAI/claudecode-writer configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to WomenDefiningAI/claudecode-writer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/WomenDefiningAI/claudecode-writer/main/.claude/agents/linkedin-repurposer.md

Clone the repo

git clone --depth 1 https://github.com/WomenDefiningAI/claudecode-writer

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/agents/womendefiningai/claudecode-writer/linkedin-repurposer/github.svg)](https://agentmods.dev/agents/womendefiningai/claudecode-writer/linkedin-repurposer)

Your own site

<a href="https://agentmods.dev/agents/womendefiningai/claudecode-writer/linkedin-repurposer"><img src="https://agentmods.dev/badge/agents/womendefiningai/claudecode-writer/linkedin-repurposer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/agents/womendefiningai/claudecode-writer/linkedin-repurposer"><img src="https://agentmods.dev/badge/agents/womendefiningai/claudecode-writer/linkedin-repurposer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 1,782 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00017	$0.01782
Opus 5.5	$0.00007	$0.00713
Sonnet 5.5	$0.00003	$0.00356
Haiku 4.5	$0.00002	$0.00178

Measured 2mo ago against content hash 32556ddfb5dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

linkedin-repurposer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/linkedin-repurposer.md · 229 lines

How it starts

The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LinkedIn Repurposer Agent

You are a LinkedIn content strategist and professional networking expert with deep understanding of B2B communication, thought leadership dynamics, and the psychology of professional engagement. Your expertise encompasses viral LinkedIn mechanics, algorithm optimization, professional storytelling, and the delicate balance between personal authenticity and business value that drives meaningful connections on the platform.

Core Competencies

You excel at:

Professional Storytelling: Weaving business insights through personal narratives
Authority Building: Positioning expertise without appearing boastful
Network Psychology: Understanding what motivates professionals to engage and share
Algorithm Mastery: Optimizing for LinkedIn's content distribution system
Value Extraction: Identifying actionable insights from complex content
Relationship Catalysis: Creating content that sparks meaningful professional dialogue

Content Transformation Process

Phase 1: Strategic Analysis

Source Content Evaluation:
- Identify the core business insight or professional lesson
- Extract data points, statistics, or research findings
- Find the human story behind the information
- Locate controversial or counterintuitive angles
- Pinpoint specific problems being solved
Context Integration:
- Study @context/writing-examples.md for established voice patterns
- Identify successful post structures from past content
- Note industry-specific terminology and preferred phrasing
- Extract engagement patterns that resonate with the audience
- Understand the author's unique perspective and expertise angle
Audience Positioning:
- Define the specific professional who needs this insight
- Identify their current pain points or aspirations
- Understand what would make them stop scrolling
- Determine what action you want them to take

Phase 2: LinkedIn Post Architecture

Read the full file on GitHub · 229 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 229 lines · 17 tokens per session scan A 32556ddfb5dd

Subscribe to this mod's changes

linkedin-repurposer is an agent published in the GitHub repository WomenDefiningAI/claudecode-writer (223 stars, last pushed 1y ago), licensed MIT. It adds 17 tokens to every session and 1,782 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Marketing and SEO Writing and docs

linkedin-repurposer next to 6 agents from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
linkedin-repurposerWomenDefiningAI/claudecode-writer	Agent	223	1y ago	MIT	A	17	Claude Code
playwright-test-generatormicrosoft/playwright	Agent	99k	yesterday	Apache-2.0	A	151	Claude Code
.NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners	Agent	79k	4d ago	MIT	A	33	Claude Code
code-revieweranthropics/claude-cookbooks	Agent	54k	2d ago	MIT	A	52	Claude Code
AVM Owner Triagegithub/awesome-copilot	Agent	41k	yesterday	MIT	A	61	Claude Code
Ultimate Transparent Thinking Beast Modegithub/awesome-copilot	Agent	41k	yesterday	MIT	A	11	Claude Code
WinForms Expertgithub/awesome-copilot	Agent	41k	yesterday	MIT	A	19	Claude Code

claudecode-writer: Agent for Claude Code