Organic LinkedIn presence, end to end, with the platform rules enforced in code. An orchestrator (context: fork) gates every request against LinkedIn's User Agreement §8.2 — refusing automation, scraping, engagement pods, bulk DMs, fake identity, fabricated proof, and named third-party automation tools, each with a compliant substitute — then routes to one of five sub-skills. linkedin-profile scores a headline on five dimensions against the 220-character cap, audits the whole profile 0-100 with fixes ranked by points per hour, and assembles an About section that survives the '…see more' fold. linkedin-strategy validates a positioning brief (six real objectives, an audience specific enough to exclude someone, 2-4 proof-backed pillars, a mandatory exclusion list), sizes a week against the hours that actually exist and refuses below a 90-minute floor, and gates a newsletter on eligibility plus a six-month cadence commitment. linkedin-content lints posts 0-100 across mechanics, hook, integrity, and accessibility — blocking on the 3,000-character cap, engagement bait, and Unicode pseudo-bold that screen readers cannot read — picks the format the material actually supports, and splits long sources into standalone units against a reuse ledger. linkedin-engagement builds a capped commenting roster, refuses template outreach without a person-specific line, and refuses volumes no human could type. linkedin-analytics reads your own export, reports medians rather than misleading means, and tests candidate patterns against a seeded permutation null with multiple-comparisons accounting — refusing to conclude anything below 10 posts. 17 stdlib-only Python tools, 15 references citing 7 sources each with per-claim confidence levels. No LinkedIn credentials, no API calls, nothing auto-sent.
By Alireza RezvaniLicense: MIT24.9k GitHub starsUpdated yesterday
Directory evidence
- Runtimes
- Claude Code
- Parsed components
- 6 skill or MCP entries
- Source updated
- Aug 25, 2026
- Manifest status
- Canonical path parsed
The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →
Install plugin
claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install linkedin@agent-plugin-marketplacePaste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.
The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.
Get the source manually
git clone https://github.com/alirezarezvani/claude-skillsClone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is marketing/linkedin/.
Plugin files
├── .claude-plugin/plugin.json├── skills/linkedin-analytics/SKILL.md├── skills/linkedin-content/SKILL.md├── skills/linkedin-engagement/SKILL.md├── skills/linkedin-profile/SKILL.md├── skills/linkedin-skills/SKILL.md└── skills/linkedin-strategy/SKILL.md
Included Skills6
Use when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis. Triggers on "why did my reach drop", "what's working on my LinkedIn", "analyze my posts", "do carousels do better for me", "should I test this", "LinkedIn analytics". Reads your own exported post data, reports medians and outlier bands, tests candidate patterns against a permutation null, and sizes a real experiment — refusing to conclude anything below 10 posts.
Use when someone wants to write, edit, or lint a LinkedIn post — a story, how-to, opinion piece, carousel script, video script, or poll — or wants an article, talk, or transcript repurposed into posts. Triggers on "write a LinkedIn post", "is this hook any good", "review my post", "turn this into LinkedIn posts", "carousel", "what format should this be". Lints posts 0-100 on mechanics, hook, integrity, and accessibility; picks the format the material actually supports; and splits long sources into standalone units with a reuse ledger.
Use when someone wants to grow reach through comments, replies, groups, or outreach on LinkedIn — a commenting roster, a connection request note, a DM or InMail, a networking plan, or a check on whether their outreach volume is safe. Triggers on "who should I engage with", "write a connection request", "cold DM", "LinkedIn outreach", "networking strategy", "how many invites can I send". Builds a weekly comment roster inside a real time budget, assembles one message at a time and refuses templates, and caps volume against LinkedIn's limits. Nothing is ever sent.
Use when someone wants their LinkedIn profile audited or rewritten — headline, About section, experience bullets, Featured, banner, recommendations — or says "fix my headline", "my profile gets views but nothing happens", "optimize my LinkedIn profile", "what should my About section say". Scores the headline on five dimensions, audits the whole profile 0-100 and ranks fixes by points per hour, and assembles an About section that survives the "…see more" fold.
Use when someone wants to grow an organic LinkedIn presence — a content strategy for a career change or consulting or thought leadership, a rewritten profile or headline, post drafts and hooks, a posting cadence or newsletter plan, connection notes and outreach, a commenting strategy, repurposing an article or talk into posts, or a read on why their reach dropped. Triggers on "grow my LinkedIn", "fix my headline", "write a LinkedIn post", "what should I post about", "LinkedIn strategy", "connection request", "my reach dropped". Forks context to route to one of five sub-skills, and refuses automation, scraping, pods, and bulk DMs before any drafting starts.
Use when someone needs a LinkedIn plan rather than a post — content pillars, positioning for a career change or consulting or thought leadership, a sustainable posting cadence, or a newsletter decision. Triggers on "what should I post about", "how often should I post", "LinkedIn content strategy", "should I start a LinkedIn newsletter", "grow my following", "90-day plan". Validates the positioning brief, sizes the week against real hours and refuses a plan that will not survive week five, and gates a newsletter against eligibility and a six-month cadence commitment.
Plugin manifests1
{
"name": "linkedin",
"description": "Organic LinkedIn presence, end to end, with the platform rules enforced in code. An orchestrator (context: fork) gates every request against LinkedIn's User Agreement §8.2 — refusing automation, scraping, engagement pods, bulk DMs, fake identity, fabricated proof, and named third-party automation tools, each with a compliant substitute — then routes to one of five sub-skills. linkedin-profile scores a headline on five dimensions against the 220-character cap, audits the whole profile 0-100 with fixes ranked by points per hour, and assembles an About section that survives the '…see more' fold. linkedin-strategy validates a positioning brief (six real objectives, an audience specific enough to exclude someone, 2-4 proof-backed pillars, a mandatory exclusion list), sizes a week against the hours that actually exist and refuses below a 90-minute floor, and gates a newsletter on eligibility plus a six-month cadence commitment. linkedin-content lints posts 0-100 across mechanics, hook, integrity, and accessibility — blocking on the 3,000-character cap, engagement bait, and Unicode pseudo-bold that screen readers cannot read — picks the format the material actually supports, and splits long sources into standalone units against a reuse ledger. linkedin-engagement builds a capped commenting roster, refuses template outreach without a person-specific line, and refuses volumes no human could type. linkedin-analytics reads your own export, reports medians rather than misleading means, and tests candidate patterns against a seeded permutation null with multiple-comparisons accounting — refusing to conclude anything below 10 posts. 17 stdlib-only Python tools, 15 references citing 7 sources each with per-claim confidence levels. No LinkedIn credentials, no API calls, nothing auto-sent.",
"version": "2.12.0",
"author": {
"name": "Alireza Rezvani",
"url": "https://alirezarezvani.com"
},
"homepage": "https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin",
"repository": "https://github.com/alirezarezvani/claude-skills",
"license": "MIT",
"skills": [
"./skills/linkedin-skills",
"./skills/linkedin-profile",
"./skills/linkedin-strategy",
"./skills/linkedin-content",
"./skills/linkedin-engagement",
"./skills/linkedin-analytics"
]
}For maintainers
If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.
[linkedin on Agent Plugins Marketplace](https://pluginsmp.com/plugins/linkedin)