ktg-plugin-marketplace/plugins/linkedin-studio

LinkedIn Studio Plugin for Claude Code

Turn your expertise into LinkedIn authority — without the blank page, the guesswork, or the generic AI slop.

Solo-maintained, fork-and-own. This plugin is a starting point, not a vendor product. Issues are welcome as signals; pull requests are not accepted. See GOVERNANCE.md for the full model and what upstream provides.

AI-generated: all code produced by Claude Code through dialog-driven development. Full disclosure →

Most experts know they should post on LinkedIn — and quietly don't. The blank editor wins. LinkedIn Studio turns that chore into a system: structured workflows that take you from idea to published, in your own voice, calibrated to how LinkedIn's topic-relevance ranking model (2026) actually distributes content. Two engines under one surface — a feed engine for short-form posts, carousels, and video scripts, and a long-form engine that runs newsletter editions and essays through a serious editorial pipeline before they ever lock. 26 commands, 19 specialized agents, 9 automated quality hooks, and a 24-document knowledge base grounded in the algorithm's real signals.

This is not a shortcut. Hand the wheel to the AI and you land where everyone who did the same lands — the forgettable middle. The plugin removes the friction; the judgment, the genuine engagement, and the effort that make content worth reading remain entirely yours.

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Table of Contents

• Why LinkedIn Studio Exists
• What Is This?
• Two Engines
• Quick Start
• Commands
• Agent Architecture
• Knowledge Base
• Skills
• Hooks & Automation
• Analytics System
• Personalization Engine
• Workflow Examples
• Content Quality Rules
• Configuration
• What This Plugin Does Not Cover
• Version History
• License

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Why LinkedIn Studio Exists

For most professionals, the hard part of LinkedIn isn't writing — it's everything around it. You have the expertise. What you don't have is a repeatable way to get it out the door, consistently, in a form the algorithm actually rewards.

The recognizable pattern of pain:

• The blank editor wins. You open LinkedIn to post, stare at the box, and close it. The idea was there; the activation energy wasn't.
• You post in bursts, then go quiet. Three posts one week, nothing for a month. The algorithm reads inconsistency as "not a creator" and quietly throttles you.
• You can't see why anything works. One post reaches 12,000 people; the next, near-identical one, reaches 200. With no model of the ranking signals, every post is a coin flip.
• Generic AI output sounds like generic AI. It doesn't sound like you, it leans on buzzwords, and LinkedIn's classifiers increasingly suppress exactly that register. "AI-assisted" only helps if it protects your voice.
• The ground moved in 2026. LinkedIn's topic-relevance model now validates your profile before distributing your content — an off-topic post or an unoptimized profile caps reach regardless of how good the writing is. Most "LinkedIn tips" predate this and are now actively misleading.

What the plugin does about it:

The pain	The plugin's answer
Blank-page paralysis	Guided workflows — from a 5-minute /linkedin:quick to a full /linkedin:pipeline — so you start from structure, not a void
Inconsistency	A scheduling queue, streak tracking, batch creation, and proactive posting reminders that keep cadence visible
Algorithm opacity	Every command is calibrated to documented topic-relevance signals; hooks gate hook-length, link-suppression, buzzwords, and topic rotation before you publish
Generic slop	Voice training learns your authentic style and flags drift; a voice-guardian hook catches AI register on the way out
The topic-relevance shift	/linkedin:profile aligns your profile to the new model first, because content distribution now depends on it

The result is not "AI writes your posts." It's a system that holds the structure, the discipline, and the algorithmic knowledge so you can focus on the one thing only you can supply — the expertise.

Tip

New here? Run /linkedin:onboarding — it walks you through profile optimization, personalization, and your first published post in one guided flow (~10 minutes).

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What Is This?

LinkedIn Studio is a complete LinkedIn content engine inside Claude Code. Instead of an empty post editor, you work through structured workflows that handle ideation, drafting, optimization, scheduling, publishing, and post-publish analytics — all calibrated to how LinkedIn's algorithm actually distributes content.

Key capabilities:

• profile/topic-relevance optimization aligned with LinkedIn's AI-first content distribution (2026 update)
• Content angle system that generates post ideas from a single topic using 8 universal thought-leadership angles
• Full content pipeline from ideation through post-publish 48-hour monitoring
• Long-form editorial pipeline — newsletter editions and essays run through skeleton, voice, fact-check, craft, resonance, and cold adversarial review gates before they lock
• Batch content creation — produce a full week of posts in one session
• Analytics pipeline — import LinkedIn CSV exports, parse into structured JSON, generate performance reports
• Voice training — learns your authentic writing style and flags drift
• Growth strategy — phase-specific guidance from foundation (0–1K followers) through authority (10K+)
• Monetization and outreach — readiness assessment, lead magnets, conference CFP templates, collaboration formats and partner pitches
• Video scripting — structured scripts for 30s/60s/90s/2min LinkedIn video
• Multi-platform repurposing — adapt LinkedIn content for Twitter/X, newsletters, blogs, slides
• A/B testing framework — design and track content experiments

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Two Engines

LinkedIn Studio is really two content engines sharing one surface. They have different speeds, different gates, and different goals.

⚡ The Feed Engine — short-form, fast, frictionless

For everyday presence. The point is velocity without losing quality: every content command auto-copies the result to your clipboard, asks at most two questions, and runs your draft through the same algorithm-aware quality gates before it ever leaves your editor.

Want to…	Command	Time
React to an article or observation	/linkedin:quick	~5 min
Write a substantial post	/linkedin:post	10–15 min
Turn a URL into a reaction post	/linkedin:react	~5 min
Build a carousel (highest engagement format)	/linkedin:carousel	~15 min
Script a video	/linkedin:video	~10 min
Fill a whole week in one sitting	/linkedin:batch	~30 min

📖 The Long-Form Engine — /linkedin:newsletter

For the pieces that build authority — newsletter editions, essays, series articles. This is what sets LinkedIn Studio apart from "AI writes your post" tools: a 16-phase pipeline where the draft has to survive a gauntlet of quality gates before it locks.

skeleton gate ──▶ voice scrub ──▶ fact-check ──▶ editorial craft gate ──▶
persona resonance ──▶ cold adversarial review ──▶ visual assets ──▶ LOCK ──▶ hook conversion
   (before prose)      (de-AI)     (sources)        (is it well-made?)
                                                  (does it land?)   (independent re-read)

Each gate exists because skipping it is expensive:

• Skeleton before prose — spine errors get caught in 15 minutes at the outline stage instead of a full day post-draft.
• Fact-check before lock — claims after the model's knowledge cutoff must be web-searched; the more convincing a draft reads, the more verification, not less.
• Editorial craft gate — an editor (not a reader) judges prose craft and narrative architecture: the blind spots a resonance sweep structurally cannot see.
• Cold adversarial review — three reviewers re-read a frozen draft with no drafting-session context, so the version that ships is the version that's actually been independently reviewed.

The cost of fixing an error in a published edition is too high — so the gates run upstream, where fixes are cheap.

Short-form lives in /linkedin:post, :quick, :react, :carousel, :video. Long-form lives in /linkedin:newsletter. /linkedin:multiplatform adapts short-form across platforms; long-form repurposing routes back to /linkedin:newsletter.

---

Quick Start

Prerequisites

• Claude Code with plugin support enabled
• Node.js 18+ (for hooks and analytics CLI; analytics requires tsx: cd scripts/analytics && npm install)

Installation

Add the marketplace and browse plugins with /plugin:

claude plugin marketplace add https://git.fromaitochitta.com/open/ktg-plugin-marketplace.git

Or enable directly in ~/.claude/settings.json:

{
  "enabledPlugins": {
    "linkedin-studio@ktg-plugin-marketplace": true
  }
}

Get Started (5 minutes)

Run the onboarding wizard — it walks you through profile, setup, and your first post in one flow:

/linkedin:onboarding

The wizard handles everything: topic-relevance profile checklist, voice and user profile setup, and a guided first post.

Already Set Up?

Goal	Command
Write a post	/linkedin:post
Quick 5-min post	/linkedin:quick
React to an article	/linkedin:react
Write a long-form edition	/linkedin:newsletter
View your stats	/linkedin:report
See all commands	/linkedin

---

Commands

All 26 commands use colon notation: /linkedin:post, /linkedin:quick, etc.

Onboarding

Command	Description
/linkedin:onboarding	Multi-step onboarding wizard — guides you through profile optimization, plugin personalization, and your first post in one flow.
/linkedin:first-post	First-post accelerator — zero to published in 10 minutes with guided hand-holding.
/linkedin:setup	Guided setup to populate empty asset templates with your real voice, case studies, and audience data.

Content Creation

Command	Description
/linkedin:post	Full interactive post creation with angle selection, format choice, and refinement. Best for substantial posts (1,200-1,800 characters).
/linkedin:quick	5-minute quick post using the 3-line formula. Target: 150-500 characters. Best for reactions, observations, tips, and questions. Also the single entry point for the 8 post-type templates (fill-in-the-blank structures).
/linkedin:newsletter	Long-form orchestrator — newsletter edition, essay, or series article end-to-end at series quality. Multi-session 16-phase pipeline with skeleton + spine-prose gates BEFORE prose, an editorial-craft gate, fact-check, persona resonance, a cold adversarial review package, and visual assets — all BEFORE lock.
/linkedin:headless-review	Cold adversarial review package — runs the 3 headless archetypes (content-reviewer, language-reviewer, fact-reviewer) + persona-reviewer (resonance/conversion) on a FROZEN draft with no drafting-session context. Step 6.5's standalone surface; run in a fresh session for maximum isolation.
/linkedin:pivot	Re-open a long-form edition after a substantive late change so cleared gates (fact-check → editorial → persona → headless) re-run before lock. Includes the pivot-detection heuristic (> 20 % word-count change or > 2 new sections).
/linkedin:pipeline	Full end-to-end content pipeline from idea to published post. Guides through ideation, drafting, optimization, scheduling, pre-engagement, publishing, and post-analysis.
/linkedin:batch	Create a full week of LinkedIn content in one session. Input one theme, output 3-5 posts with varying angles and formats. Writes to scheduling queue.
/linkedin:calendar	View and manage the post scheduling queue — upcoming, overdue, published — and run the publish action (mark a scheduled post as published, update state + streak tracking, surface the first-hour engagement plan).
/linkedin:carousel	Structured multi-slide carousel generator with slide-by-slide copy and visual layout guidance. Optionally generates slide images via mcp-image.
/linkedin:video	Video script generator for 30s, 60s, 90s, or 2-minute LinkedIn videos with pacing and visual cues.
/linkedin:multiplatform	Adapt LinkedIn content for Twitter/X threads, newsletter sections, blog posts, presentation slides, and YouTube scripts.
/linkedin:react	URL-to-post pipeline — paste an article, research paper, or news link and generate a reaction post.

Analytics

Command	Description
/linkedin:analyze	Analyze content performance and troubleshoot engagement issues. Diagnoses algorithm penalties, profile-content mismatches, and reach drops.
/linkedin:audit	Periodic content strategy audit. Reviews top/bottom posts, topic distribution, format mix, and engagement trends. Run quarterly.
/linkedin:report	Generate weekly performance report from imported analytics data. Shows key metrics, top performers, trends, and actionable alerts.
/linkedin:import	Import LinkedIn analytics CSV export into structured JSON. Auto-detects files in ~/Downloads, parses CSV, detects anomalies.
/linkedin:competitive	Competitive analysis of other thought leaders in your niche. Analyzes posting frequency, content types, hooks, and identifies differentiation opportunities.
/linkedin:ab-test	Design and manage A/B content tests. Track experiments across post variations.

Strategy

Command	Description
/linkedin:strategy	Growth strategy + authority building. Phase-specific guidance from foundation (0-1K) through authority establishment (10K+), trajectory-aware adjustments, and signature-content compounding for Phase 2+. The single growth/authority entry point — /linkedin:profile owns topic-relevance alignment.
/linkedin:monetize	Monetization strategy with scored readiness assessment, stage-specific action plans, lead magnet blueprints, DM conversion workflows, and revenue dashboards.
/linkedin:outreach	Outreach orchestrator covering both collaborations and speaking opportunities under one paradigm: readiness assessment (collab thresholds + 100-pt speaker scorecard), partner scoring (25-pt rubric), event/CFP search with Nordic/European conference calendar, 12 collaboration formats across 4 maturity tiers, 4 talk abstract templates, speaker bio variants, co-creation production workflow, unified pipeline tracker, and quarterly results dashboard.

Profile & Setup

Command	Description
/linkedin:profile	profile/topic-relevance optimization checklist. Audits About section, Experience, Headline, content history alignment, and network patterns.
/linkedin:setup	Guided setup to populate asset templates with real data. 6 sub-workflows: voice samples, case studies, frameworks, post analysis, demographics, user profile. Calculates personalization score.
/linkedin	Main router. Shows posting status (streak, weekly progress) and lists all available commands with contextual guidance.

---

Agent Architecture

The plugin delegates specialized work to 19 purpose-built agents. Each agent has its own model assignment, color identity, and focused responsibility.

Agent	Model	Color	Primary Responsibility
content-optimizer	Sonnet	Blue	Optimize posts against algorithm signals, hooks, CTAs
strategy-advisor	Sonnet	Green	Growth strategy and phase-specific guidance
analytics-interpreter	Sonnet	Yellow	Pattern discovery + weekly/monthly performance reports (interpret/report modes)
engagement-coach	Sonnet	Magenta	5x5x5 + first-hour tactics + CEA commenting + target selection
content-planner	Sonnet	Cyan	Weekly/monthly content calendars and mix enforcement
network-builder	Sonnet	Teal	Strategic networking, connection scoring, DM templates
content-repurposer	Sonnet	Purple	Format conversion and evergreen content refresh
trend-spotter	Sonnet	White	Trending topics, opportunity scoring, first-mover assessment
voice-trainer	Sonnet	Pink	Voice profile building and drift detection
differentiation-checker	Sonnet	Gray	Originality scoring and commodity content detection
post-feedback-monitor	Haiku	Lime	Post-publish 48h monitoring and real-time interventions
video-scripter	Sonnet	Violet	Video script creation with pacing and visual cues
fact-checker	Opus	Brown	Factual-claim verification against primary/credible sources, post-cutoff web-search mandate (longform)
editorial-reviewer	Opus	Orange	Editor's craft gate (Step 5.5, before persona sweep): prosa-håndverk + narrativ-arkitektur, ≤10 flags BLOCK/REWORK/NICE as direction, operator-gated via SendUserFile; mirrors Maskinrommet §C2 (longform)
persona-reviewer	Opus	Olive	Reader-persona skeleton (before prose) + resonance (before lock) + hook-conversion (after lock) gate, blocking hard-fail list (longform)
voice-scrubber	Opus	Red	De-AI scrub + Norwegian-chronicle voice-drift correction; gold standard = approved Norwegian editions, not the English post corpus (longform)
content-reviewer	Opus	Maroon	(Step 6.5 — cold/headless) Argument integrity: logical holes · unsupported assumptions · contradiction · missing concretization · unanswered objection; ≤8 flags; refuses drafting-session framing as context pollution (longform)
language-reviewer	Opus	Navy	(Step 6.5 — cold/headless) Norwegian language: verbatim repetition · anglicisms · stiff register · self-contradiction · clang/rhythm; ≤10 flags; deliberate cold re-take of editorial's prose axis (longform)
fact-reviewer	Opus	Gold	(Step 6.5 — cold/headless) Cold re-verification on the frozen/pivoted version (web search): verifiable claims · quote precision · number attribution · source quality; 🔴/🟡/🟢 + pivot-risk; deliberate redundancy with fact-checker (longform)

Content Pipeline

Agents collaborate across the end-to-end content lifecycle:

trend-spotter --> content-planner --> differentiation-checker --> content-optimizer --> [PUBLISH]
                       |                                                                    |
                  voice-trainer                                                    engagement-coach
                                                                                  (5x5x5 + first-hour
                                                                                   + CEA commenting)
                  analytics-interpreter
                  (interpret + report modes)

Parallel support agents: strategy-advisor, analytics-interpreter, network-builder, content-repurposer, video-scripter.

Longform quality gates (newsletter): persona-reviewer (skjelett) run BEFORE prose (Step 2.5) → voice-scrubber de-AI / chronicle-voice scrub (Step 4) → fact-checker (Step 5) → editorial-reviewer craft gate run BEFORE the persona sweep (Step 5.5) → persona-reviewer (resonance) run BEFORE lock (Step 6) → headless adversarial review package run COLD BEFORE lock (Step 6.5: content-reviewer + language-reviewer + fact-reviewer + persona-reviewer) → persona-reviewer (conversion) run AFTER lock on the hook (Step 9).

Note (agent invocation + reload): Commands invoke agents by their namespaced type — subagent_type: linkedin-studio:<name>, never the bare name. And a newly added agent file under agents/ only becomes invokable after a Claude Code session reload (the plugin agent set is built at session start). Add the agent, then reload before invoking it.

Which Agent Do I Need?

Scenario	Agent
"Make this post better"	content-optimizer
"What should I post about?"	content-planner, trend-spotter
"Is this original enough?"	differentiation-checker
"Plan my week's content"	content-planner
"How did I do this week?"	analytics-interpreter (report mode)
"Analyze my LinkedIn data"	analytics-interpreter (interpret mode)
"Help me engage more"	engagement-coach
"Who should I comment on?"	engagement-coach
"Build my network"	network-builder
"Does this sound like me?"	voice-trainer
"Repurpose my best post"	content-repurposer
"What's trending in my field?"	trend-spotter
"How do I monetize?"	strategy-advisor
"How is my latest post doing?"	post-feedback-monitor
"How personalized is my plugin?"	/linkedin:setup
"Write a LinkedIn video script"	video-scripter

---

Knowledge Base

The plugin includes 24 reference documents covering the full LinkedIn thought leadership domain:

Category	Document	When to Use
Algorithm	algorithm-signals-reference.md	Profile setup, troubleshooting reach
Angles	thought-leadership-angles.md	Choosing post angle (8 universal angles)
Engagement	engagement-frameworks.md	Writing hooks, CTAs, 5x5x5 method
Formats	linkedin-formats.md	Choosing content format
Growth	linkedin-growth-playbook-2025-2026.md	Strategy deep-dive
Monetization	linkedin-monetization-strategies.md	Revenue planning
Newsletter	newsletter-strategy-guide.md	Newsletter strategy (5,000+ followers)
Articles	articles-strategy-guide.md	Long-form content
Roadmaps	growth-roadmaps.md	Monthly planning
Low-frequency	low-frequency-posting-strategy.md	2-3x/week strategy
Collaborations	collaborations-guide.md	Partnership strategy
Opportunities	opportunity-generation.md	Business development
Analytics	analytics-tools-guide.md	Finding your edge
Troubleshooting	troubleshooting-guide.md	When reach drops
URLs	url-processing-templates.md	Converting external content
AI Content	ai-content-framework.md	AI-specific angles
First Comment	first-comment-strategy.md	Comment templates and timing
Visual Style	linkedin-visual-style.md	Image and carousel specs
Polls	poll-strategy-guide.md	Poll question types and follow-up
A/B Testing	ab-testing-framework.md	Content experiment design
Scheduling	scheduling-strategy.md	Optimal posting times and rotation
Trajectory	trajectory-strategy-adjustments.md	Growth trajectory adjustments
Video	video-strategy-guide.md	LinkedIn video best practices
Glossary	glossary.md	38 plugin-specific terms

---

Skills

Six domain-specific skills organize the plugin's knowledge and route commands to the right context:

Skill	Domain	Commands Routed
linkedin-studio	Router + shared knowledge (algorithm, quality rules)	/linkedin, /linkedin:setup
linkedin-content-creation	Posts, batch, pipeline, video, calendar, newsletter	/linkedin:post, :quick, :pipeline, :batch, :calendar, :video, :multiplatform, :newsletter, :carousel
linkedin-analytics	Analysis, reporting, import, A/B testing	/linkedin:analyze, :audit, :import, :report, :ab-test
linkedin-strategy	Growth, authority (absorbed), competitive, monetization	/linkedin:strategy, :competitive, :monetize
linkedin-networking	Engagement, collaborations, speaking (all in outreach)	/linkedin:outreach
linkedin-voice	Voice training, profile optimization, differentiation	/linkedin:profile

---

Hooks & Automation

9 hooks across 7 events provide automated quality gates, state management, and proactive reminders. All hooks are Node.js (.mjs) for cross-platform support.

Event	Type	Purpose
SessionStart	command	Load persistent state, posting metrics, REMEMBER.md context, and 10K milestone tracker
PreToolUse (Write|Edit)	command	Content quality gate — hook length, link check, tone, post length
PreToolUse (Write|Edit)	command	Voice guardian — AI authenticity check and voice matching
PreToolUse (Write|Edit)	command	Topic rotation gate — no back-to-back same pillar, no pillar >50% in 14-day window
Stop	command	Update state file with posting metrics and pre-publish reminders
UserPromptSubmit	command	LinkedIn context enrichment based on prompt keywords (two-tier matching)
PostToolUse (Write)	command	Post-creation automation: alternative hooks, posting time, 5x5x5 reminder
PreCompact	command	Preserve critical LinkedIn context during context compaction
Notification (idle_prompt)	command	Proactive posting reminders: streak risk, weekly goals, optimal windows (rate-limited 30min)

How Hooks Collaborate

PreToolUse hooks use a shared content-gatekeeper (content-gatekeeper.mjs) that first checks isLinkedInContent() before injecting the relevant prompt. This prevents false positives on non-LinkedIn file edits.

Session markers (/tmp/linkedin-hooks/session-active) are set when LinkedIn content is detected. The Stop hook only fires state updates if this marker exists (max 12h staleness). The Notification hook rate-limits via a separate marker with a 30-minute cooldown.

Note

Prompt content lives in hooks/prompts/*.md and is loaded dynamically at runtime. The compiled hooks.json is generated from hooks.template.json — do not edit it directly.

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Analytics System

A Node.js CLI tool for parsing LinkedIn CSV exports into structured JSON.

Workflow

1. Export analytics CSV from LinkedIn
2. Place in assets/analytics/exports/ (or use auto-detect from ~/Downloads)
3. Run /linkedin:import to parse into structured JSON
4. Run /linkedin:report to generate weekly performance reports

CLI Usage

ANALYTICS_ROOT="${CLAUDE_PLUGIN_ROOT}/assets/analytics" \
  node --import tsx "${CLAUDE_PLUGIN_ROOT}/scripts/analytics/src/cli.ts" import <file>

ANALYTICS_ROOT="${CLAUDE_PLUGIN_ROOT}/assets/analytics" \
  node --import tsx "${CLAUDE_PLUGIN_ROOT}/scripts/analytics/src/cli.ts" report --week <W>

ANALYTICS_ROOT="${CLAUDE_PLUGIN_ROOT}/assets/analytics" \
  node --import tsx "${CLAUDE_PLUGIN_ROOT}/scripts/analytics/src/cli.ts" trends --period <P> --metric <M>

Storage

assets/analytics/
├── exports/         # Raw CSV from LinkedIn (drop files here)
├── posts/           # Imported post data as JSON
└── weekly-reports/  # Generated weekly reports

Agents that consume analytics data: analytics-interpreter (interpret/report modes).

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Personalization Engine

The plugin tracks how well you've populated asset templates with your own data. A higher personalization score means more tailored content output.

Scoring Categories (100 points total)

Category	Weight	Source
Voice samples	25	assets/voice-samples/
User profile	20	config/user-profile.local.md
Case studies	15	assets/case-studies/
Frameworks	10	assets/frameworks/
High-engagement posts	10	assets/examples/
Demographics	8	assets/audience-insights/
Engagement patterns	7	assets/audience-insights/
Post templates	5	assets/templates/

Run /linkedin:setup to see your current score and walk through guided workflows for each category. The score is also displayed in your session status line at startup.

Assets Directory

Directory	Contents
templates/	Post type templates, carousel blueprints, article template, content calendar
checklists/	Quality scorecard for pre-publish checks
examples/	High-engagement post examples
voice-samples/	Your authentic voice reference (add your own)
audience-insights/	Demographics and engagement patterns
case-studies/	Case study template for your real stories
frameworks/	Framework template for your methodologies
analytics/	Imported data, weekly reports (gitignored)
drafts/	Post scheduling queue and weekly drafts (gitignored)

---

Workflow Examples

1. Sunday Content Prep

/linkedin:batch
> Theme: AI adoption in government IT

# Creates 3-5 posts with varying angles and formats
# Posts are added to the scheduling queue

/linkedin:calendar
# Review the upcoming week's schedule

2. Quick React Post (5 minutes)

/linkedin:quick
> Just saw Microsoft announce Copilot Studio autonomous agents —
> this changes everything for low-code teams

3. A Long-Form Edition, Done Right

/linkedin:newsletter
> Write the next edition of my series on AI governance in the public sector

# Multi-session: skeleton gate → spine prose → voice scrub → fact-check →
# editorial craft gate → persona resonance → cold adversarial review →
# visual assets → lock → hook conversion. Resumes by phase across sessions.

4. Import Analytics and Review Performance

/linkedin:import
> ~/Downloads/linkedin-analytics-2026-02.csv

/linkedin:report
> Show me last week's performance

/linkedin:audit
> Full quarterly review

5. Grow from 2K to 5K Followers

/linkedin:strategy
> I have about 2,500 followers and want to reach 5K

/linkedin:competitive
> Analyze the top 5 thought leaders in Microsoft AI for government

6. Repurpose a Viral Post

/linkedin:multiplatform
> Take my best-performing post and adapt it for a Twitter thread
> and 3 presentation slides

---

Content Quality Rules

The plugin enforces quality standards through hooks and agent behavior:

Rule	Threshold	Enforcement
Hook length	110-140 characters	PreToolUse quality gate
Post length (standard)	1,200-1,800 characters	PreToolUse quality gate
Post length (quick)	150-500 characters	PreToolUse quality gate
No external links in body	0 links	PreToolUse quality gate (body links correlate with lower reach)
No corporate buzzwords	Blocklist: leverage, synergy, paradigm shift, thought leader, disruptive, value proposition, ecosystem, holistic approach	PreToolUse quality gate
Topic alignment	Must align with 5 core expertise areas	topic-relevance signal check
Topic rotation	No back-to-back same pillar; no pillar >50% in 14 days	Topic rotation gate (warn-only)
Voice consistency	AI authenticity check + voice matching	Voice guardian hook

---

Configuration

User Profile

cp config/user-profile.template.md config/user-profile.local.md

Edit with your name, expertise areas, target audience, voice preferences, and LinkedIn goals. The more detail you provide, the more personalized the output.

State File

The plugin tracks posting metrics in ~/.claude/linkedin-studio.local.md:

---
last_post_date: 2026-01-28
posts_this_week: 2
weekly_goal: 3
current_streak: 12
current_week: "2026-W05"
follower_count: 0
follower_target: 10000
target_date: "2026-12-31"
next_planned_topic: ""
---

State is automatically initialized on first session start (from config/state-file.template.md) and updated by the Stop hook after each content session.

Post Queue

Scheduled posts are tracked in assets/drafts/queue.json:

• Managed by queue-manager.mjs (imported by session-start, posting-reminder, and commands)
• Status flow: draft -> scheduled -> published (or cancelled)
• Created by /linkedin:batch and /linkedin:pipeline
• Viewed via /linkedin:calendar
• Transitioned (marked as published) via the /linkedin:calendar publish action

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What This Plugin Does Not Cover

Area	Why	Alternative
LinkedIn API integration	No official API for content posting	Copy/paste from generated drafts (auto-copied to clipboard)
Real-time analytics	LinkedIn doesn't provide streaming data	Periodic CSV import via /linkedin:import
Engagement automation	Automated commenting violates LinkedIn ToS	Manual engagement guided by /linkedin:outreach
Profile editing	Plugin generates recommendations, not API calls	Apply changes manually on LinkedIn
Team/multi-user workflows	Designed for individual thought leaders	Enterprise LinkedIn tools
Content scheduling via API	No official scheduling API	Queue management with manual posting via /linkedin:calendar (publish action)

---

Version History

Version	Date	Highlights
3.1.0	2026-05-29	Adversarial review package (Endring 9). New /linkedin:headless-review command + Step 6.5 (headless-review) in /linkedin:newsletter: three cold/headless archetypes — content-reviewer (argument), language-reviewer (Norwegian), fact-reviewer (cold re-verification + pivot-risk) — plus persona-reviewer (resonance/conversion), all with NO drafting-session context. New /linkedin:pivot command + pivot-detection gate (> 20 % word-count / > 2 new sections re-opens cleared gates before lock). Per-artifact personas (articles.NN.personas). Pipeline 15 → 16 phases; 24 → 26 commands; 16 → 19 agents; additive personas/pivots/headlessReview state. Backward-compatible; reload required for the new agents.
3.0.0	2026-05-29	Renamed linkedin-thought-leadership → linkedin-studio ("LinkedIn Thought Leadership" → LinkedIn Studio). Breaking (slug + agent namespace linkedin-studio:<agent> + runtime state path ~/.claude/linkedin-studio.local.md all change; reinstall required, state migrated in place), but functionality byte-identical to v2.4.0. The /linkedin:* commands are unchanged (frontmatter-namespaced, slug-independent). Catch-all skill dir renamed to match (skills/linkedin-studio/); the five functional skills unchanged.
2.4.0	2026-05-29	Editor's craft gate as an explicit pipeline phase. New editorial-reviewer agent (Opus) + Step 5.5 — Editorial review in /linkedin:newsletter (between fact-check and the persona sweep): two axes — prosa-håndverk (em-dash density, verbatim repetition, postulated numbers, contradictions, versal-tic) + narrativ-arkitektur (concrete instantiation, theory-anchored hypotheses, series-title symmetry, equal action per addressee, un-overloaded conclusion); ≤10 flags BLOCK/REWORK/NICE as direction; operator-gated via SendUserFile; mirrors Maskinrommet §C2. Motivated by Del 4 (every persona PASS, yet 8 fresh editor points, ~6/8 craft/architecture blind spots). editorial-review phase + additive editorialReview state. Pipeline 14 → 15 phases; 15 → 16 agents. New agent + fasit fixture + lint test the only new files; commands (24) unchanged.
2.3.0	2026-05-28	Visual assets as an explicit pipeline phase. New Step 7.5 — Visual assets in /linkedin:newsletter (between annotation and lock): cover (+ optional inline figures) or carousel deck, generated (default mcp-image; external cover-raw.png accepted) and operator-gated via SendUserFile BEFORE lock so build-linkedin.mjs picks up cover.png without a post-lock re-render. Explicit format: "carousel" branch reusing build-carousel.mjs. New config/image-credit-caption.template.md; additive visualAssets state + naming convention (cover.png / cover-v<N>-kandidat.png / cover-raw.png / fig<N>.png). Pipeline 13 → 14 phases. Doc/orchestration-only (no new code); commands (24) + agents (15) unchanged.
2.2.0	2026-05-28	Longform gates hardened (2nd production run). Persona gate blocking with explicit hard-fail list (primær mistet meg / doesn't own action / sjargong-mur / modell-navne-katalog → BLOCK; «JA med forbehold» = NEI). Fact-check post-cutoff web-search mandate + high-frequency-error checklist. New voice-scrubber agent (Opus): de-AI scrub + Norwegian-chronicle voice-drift, gold standard = approved Norwegian editions (NOT the English post corpus). Render+annotate operator gates (Steps 2.5/3a). Edition state reconciled with STATE.md (ONE-system); edition-HANDOVER.template.md deleted. 14 → 15 agents; commands unchanged (24).
2.1.0	2026-05-28	Skeleton gate BEFORE prose in /linkedin:newsletter. New Step 2.5 (skeleton + section pitch, operator-gate + persona-skjelett-sweep) and Step 3a (spine prose, operator-gate) split the old Step 3 into pre-prose stages with their own gates. New persona-reviewer mode (skjelett). Pipeline grows 11 → 13 phases; commands and agents unchanged in count (24, 14). Encodes the Maskinrommet writing-contract §A discipline (premiss / problem / anbefaling / gevinst / vei videre) into the pipeline. Empirically motivated by the Seres-serien Del 3 + Del 4 spine-rework cost.
2.0.0	2026-05-28	Full-spectrum content engine. /linkedin:newsletter long-form orchestrator with multi-session edition-state, fact-check + persona-sweep gates BEFORE lock. New agents: fact-checker, persona-reviewer (both Opus). Render pipeline migrated in-plugin with self-hosted OFL-1.1 fonts. Net-fewer surface: 27 → 24 commands (5 removed, 2 added), 16 → 14 agents (4 merged, 2 added). Router gating on monetize/outreach (unlocks at ~1K). /linkedin:import delegates analysis to /linkedin:report.
1.2.0	2026-04-11	Friction reduction release. Auto-clipboard on all content commands, reduced interactive steps (max 2 per post), deterministic state management (state-updater.mjs), MCP image carousel pipeline, progressive onboarding, iCal calendar integration for batch scheduling, auto-prune content history (90 days).
1.1.0	2026-04-08	Q2 feature release. 27 commands (+onboarding, +carousel). Week-rollover automation, voice drift scoring, industry content matrix, multi-URL react, day-of-week heatmap, month-over-month reports.
1.0.0	2026-04-07	Public release. 25 commands, 16 agents, 9 hooks, 6 skills, 24 reference docs. Agent model tiering (Sonnet/Haiku), all scripts Node.js, comprehensive documentation.
0.6.0	2026-02-07	First formal version. 20 commands, 15 agents, 8 hooks, analytics system, profile/topic-relevance optimization, content matrix system, personalization engine, 20 reference documents.

See CHANGELOG.md for full details and known gaps.

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License

This project is licensed under the MIT License.

The plugin architecture, content strategies, and algorithm analysis are original work. LinkedIn is a trademark of LinkedIn Corporation.

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