ktg-plugin-marketplace/plugins/linkedin-thought-leadership

LinkedIn Thought Leadership Plugin for Claude Code

Build authentic LinkedIn authority through algorithmic understanding, strategic consistency, and AI-assisted content creation.

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 →

A comprehensive Claude Code plugin that turns LinkedIn from a chore into a full-spectrum content engine — short-form feed posts, carousels, video scripts, and long-form newsletter editions. v2.0.0 consolidated the surface (27 → 24 commands, 16 → 14 agents) and added /linkedin:newsletter as a multi-session long-form orchestrator with fact-check + persona-sweep gates BEFORE lock. v2.1.0 adds two more gates BEFORE prose to /linkedin:newsletter — a skeleton gate (Step 2.5) and a spine-prose gate (Step 3a) — encoding the Maskinrommet writing-contract §A discipline (premiss / problem / anbefaling / gevinst / vei videre) into the pipeline itself, so spine errors get caught in minutes at the skeleton stage instead of hours at the resonance stage or a full day post-lock. v2.2.0 hardened the longform gates with the lessons from the next production run: blocking persona hard-fails (primær «mistet meg» / doesn't own the action / jargon wall / model-name catalog → BLOCK), a post-cutoff fact-check mandate, a new Norwegian-chronicle de-AI voice-scrubber agent, render+annotate operator gates, and edition state reconciled with the global STATE.md continuity system. v2.3.0 makes visual assets an explicit pipeline phase — Step 7.5 (visual-assets) between annotation and lock: the cover (+ optional inline figures) or a carousel deck is generated and operator-gated before lock, so the renderer picks up cover.png without a post-lock re-render. v2.4.0 adds an editor's craft gate — new Step 5.5 (editorial-review) between fact-check and the persona sweep: a new editorial-reviewer agent (Opus) judges craft (prose-craft + narrative-architecture), not reader-response, returning ≤10 flags (BLOCK / REWORK / NICE) operator-gated via SendUserFile so the personas measure resonance instead of stumbling on craft noise (pipeline 14 → 15 phases). 24 slash commands, 16 specialized agents, 9 automated hooks, and a 24-document knowledge base grounded in LinkedIn's actual algorithm signals. Updated for the January 2026 360Brew algorithm change, where LinkedIn now validates your profile before distributing content.

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Table of Contents

• What's New in v2.4.0
• What's New in v2.3.0
• What's New in v2.2.0
• What's New in v2.1.0
• What's New in v2.0.0
• What Is This?
• 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

---

What's New in v2.4.0

An editor's craft gate becomes an explicit pipeline phase. The Del 4 production run exposed a gap the existing gates could not see: the persona resonance sweep returned 15 flags across three personas and every persona reported PASS / ready-to-publish — yet the editor (KTG) found eight fresh editorial points on first reading, and only ~25 % overlapped anything the personas had touched. The other six were craft and narrative-architecture blind spots no agent measured. persona-reviewer measures reader response (does it land?); nothing measured prose craft or narrative architecture (is it well-made?). v2.4.0 adds the missing role.

• New editorial-reviewer agent (Opus, orange) — an editor, not a reader. Two axes: prosa-håndverk (em-dash density, verbatim repetition, postulated numbers without source/hedge, internal contradictions, versal-tic — mostly grep-able) and narrativ-arkitektur (concrete instantiation, theory-anchored hypotheses, series-title symmetry, equally-usable action per addressee, an un-overloaded conclusion). Returns ≤10 flags as direction — never rewritten copy (the jury judges, the writer writes) — each with a quote/line-ref and a severity: BLOCK / REWORK / NICE. The checklist is the operationalized mirror of the Maskinrommet writing-contract §C2. (New agent — requires a session reload before it is invokable.)
• New Step 5.5 — Editorial review (commands/newsletter.md), between fact-check (Step 5) and the persona sweep (Step 6). Runs a single foreground editorial-reviewer call, surfaces the report to the operator via SendUserFile (the same operator-gate pattern as Steps 2.5/3a/7.5), folds approved flags in by tightening → v(n+1), and optionally re-runs on the cleaned version.
• Why before the persona sweep, not after — the personas measure response. If the prose is locally messy (an em-dash thicket, a postulated number, a repeated phrase) the persona flags become noise — the reader stumbles on the craft defect instead of judging mobilization. Clean the craft first, and Step 6 measures what it was built to measure.
• Supplementary, not a replacement — persona-reviewer is unchanged. One agent measures craft (5.5), one measures response (6); the role boundary is sharp (editorial-reviewer never flags "this won't resonate"; persona-reviewer never flags em-dash density).
• editorial-review phase + additive editorialReview state in config/edition-state.template.json. Pipeline grows 14 → 15 phases; resumption stays deterministic (factcheck-sweep now resumes at Step 5.5).
• Fasit fixture + structural lint — agents/fixtures/editorial-reviewer-cases.md encodes the Del 4 v5 gold standard (KTG's eight points mapped to the two axes + severities; 6/8 editorial-only blind spots), with agents/__tests__/editorial-reviewer-fixture.test.mjs asserting its shape (7 tests, green). The calibration target for a live run (which needs a session reload + the Del 4 v5 draft).

Doc/orchestration-only for the wiring — the new agent, its fasit fixture, and the lint test are the only new files; no new runtime code. 16 agents (was 15). Commands (24) unchanged. Backward-compatible: the only state-shape change is additive.

---

What's New in v2.3.0

Visual assets become an explicit pipeline phase. Until now, images (cover + inline figures) were produced ad-hoc outside the /linkedin:newsletter pipeline and referenced by hand — even though a cover is mandatory and has to coordinate with the text. v2.3.0 adds Step 7.5 — Visual assets between annotation (Step 7) and lock (Step 8), so visuals are resolved before the edition locks.

• New Step 7.5 — Visual assets (commands/newsletter.md). Decides image needs from the article type (method-heavy → 1–2 inline figures; diagnosis-heavy → cover only), writes a per-image brief, generates, runs an operator-gate, and records credit + caption. It runs before lock on purpose: render/build-linkedin.mjs picks up linkedin/NN/cover.png + the edition-config credit/caption at lock, so generating images after lock would force a re-render and break the lock.
• Two generation routes, no lock-in — default mcp__mcp-image__generate_image (Nano Banana Pro) writing cover-v<N>-kandidat.png, or an external route (DALL·E / Midjourney / photographer) via a cover-raw.png the operator drops in. The interface is pluggable (path-in / path-out); mcp-image is the default, not a hard dependency.
• Operator-gate = the Step 2.5/3a pattern, for images — every candidate is surfaced via SendUserFile for side-by-side comparison; on approval the chosen candidate is copied to the fixed cover.png name that the renderer reads.
• Explicit carousel branch — format: "carousel" editions render a typografisk slide-deck via the existing render/build-carousel.mjs instead of cover+inline.
• New config/image-credit-caption.template.md — cover motif + credit + caption table (honest-about-AI credit per the verification duty), modelled on the established series convention. Documents the cover.png / cover-v<N>-kandidat.png / cover-raw.png / fig<N>.png naming.
• visual-assets phase + additive visualAssets state in config/edition-state.template.json. Pipeline grows 13 → 14 phases; resumption stays deterministic (annotation now resumes at Step 7.5).

Doc/orchestration-only — no new code. Commands (24) and agents (15) unchanged. Backward-compatible: the only state-shape change is additive.

---

What's New in v2.2.0

Longform gates hardened — the second production run (Seres-serien) surfaced six concrete weaknesses; v2.2.0 closes all of them. A chronicle built as a model/name catalog passed review (flags were read as notes, not stop-signs) and nearly shipped; the rewrite was better but introduced fresh factual errors. The gates now make both failure modes blocking.

• Persona gate is blocking, with an explicit hard-fail list (agents/persona-reviewer.md, config/personas.template.md). The bar is the primær reader's clean JA — «JA med store forbehold» = NEI. Hard fails (= rewrite, not annotate): primær «mistet meg», primær doesn't own the action, sjargong-mur, modell-/navne-katalog. Any one → BLOCK regardless of the other axes.
• Fact-check is orthogonal to narrative strength (agents/fact-checker.md). The more convincing a draft reads, the more verification — not less. Claims dated after the model's knowledge cutoff MUST be web-searched (never confirmed from memory), plus an explicit checklist for the high-frequency error types (person titles, org-varying "standards", over-credited studies, source scope, founding/release years).
• New voice-scrubber agent (Opus) — aggressive de-AI scrub (Pass 1, objective: «la meg være ærlig», reflex rule-of-three, em-dash-spam, self-referential overhead, modell-/navne-katalog) + voice-drift correction (Pass 2, calibrated). Gold standard = the approved Norwegian editions, NOT the English authentic-voice-samples.md (which forbids the em-dash and would degrade chronicle voice). Wired into Step 4 of /linkedin:newsletter. (New agent — requires a session reload before it is invokable.)
• Render+annotate operator gates (commands/newsletter.md Steps 2.5, 3a). The operator review is HTML annotation in the browser (render/build-html.mjs → file:// link), not a multiple-choice prompt — for every write deliverable, skeleton included. AskUserQuestion becomes a receipt + fallback.
• Edition state reconciled with STATE.md (ONE-system). edition-HANDOVER.md is gone; narrative state lives in <serie>/STATE.md (overwritten each phase, auto-injected by the session-start hook), machine state (fact-check log, persona verdicts, immutable rules) in edition-state.json. config/edition-HANDOVER.template.md deleted.
• Voice-profile + longform-rules avoid-patterns — modell-/navne-katalog, completeness-over-reader-action, and self-referential overhead openings added to references/longform-quality-rules.md (rules 1 + 3) and config/user-profile.template.md.

15 agents (was 14). No command-count change (24). Backward-compatible: existing editions resume by currentPhase; the only state-shape change is additive (personaSweep.skeleton, immutableRules).

---

What's New in v2.1.0

Skeleton gate before prose in /linkedin:newsletter — the single most expensive failure mode in long-form (spine errors caught post-prose) is now gated before the first sentence is written. Empirically motivated by the Seres-serien Del 3 + Del 4 production (~1 day lost to spine rework that a 15-minute skeleton gate would have caught).

• New Step 2.5 — Skeleton + section pitch — writes <serie>/NN-skjelett.md with the five-line spine (premiss / problem / anbefaling / gevinst / vei videre) + one-line section pitches. Operator-gate (JA / REVIDER / NEI) AND parallel persona-skjelett-sweep must both return JA before the pipeline can advance. No prose is written until the spine is right.
• New Step 3a — Spine prose — one paragraph per section against the gated skeleton, ~20–30 % of final edition length. Operator-gate on whether the axis lands now that there is prose on it. The old Step 3 (Draft) is split into 3a (spine) and 3b (full expansion); 3b owns the multi-session draft-cursor logic, 3a is short enough to restart on interruption.
• New persona-reviewer mode: skjelett — third mode alongside resonans (before lock) and konverter (after lock). Five spine axes (Premiss / Problem / Anbefaling / Gevinst / Vei videre) scored HOLDER / TVILER / MANGLER, ≤3 direction-only flags, per-pitch section-pay-in check. Reads the skeleton + pitches only — no prose.
• Two new phase strings in edition-state.template.json — skeleton-pitch + spine-prose. The pipeline grows from 11 to 13 phases; resumption is deterministic across every new phase boundary.
• Rule 8 — Skjelett før prosa in references/longform-quality-rules.md — codifies the skeleton-before-prose pre-condition that all other quality rules implicitly rely on.

Backward-compatible: existing editions with currentPhase: "research" now resume at Step 2.5 (was Step 3) — an intended deterministic improvement; the contract on every other phase is bit-for-bit unchanged.

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What's New in v2.0.0

Full-spectrum content engine — feed posts AND long-form newsletter editions in one cohesive surface, with net-fewer commands.

• Long-form /linkedin:newsletter orchestrator — multi-session pipeline (load → calibrate → research fan-out → draft → consistency → fact-check sweep → persona sweep → lock → delivery → hook-gate → schedule) with maintained edition-state across sessions. Supports newsletter editions, essays, and series articles
• Two new longform-quality gate agents — fact-checker (Opus, verifies every factual claim against primary sources) and persona-reviewer (Opus, evaluates reader-persona resonance + hook-conversion). Both run BEFORE lock — the cost of fixing an error in a published edition is too high
• Render pipeline migrated into the plugin — render/build-html.mjs, build-pdf.mjs, build-linkedin.mjs, build-carousel.mjs + self-hosted fonts (Newsreader, Inter, JetBrains Mono) under OFL-1.1. No more cross-repo render dependency
• Persona library — config/personas.template.md lets you define reader personas with knowledge level, time-pressure, and resonance criteria. persona-reviewer uses these to evaluate every long-form draft
• Edition-state schema — assets/editions/<slug>/state.json tracks a long-form piece across many sessions (research notes, draft revisions, fact-check status, persona-review status, lock state)
• Net surface reduction — 27 → 24 commands (5 removed: templates, publish, authority, collab, speaking absorbed into existing commands; 2 added: newsletter, outreach). 16 → 14 agents (4 merged: content-tracker, personalization-scorer, performance-reporter, comment-strategist absorbed into analytics-interpreter + engagement-coach; 2 added: fact-checker, persona-reviewer)
• Analytics consolidation — analytics-interpreter now has interpret + report modes (replaces standalone performance-reporter); engagement-coach now owns 5x5x5 + first-hour tactics + CEA commenting + target selection + daily routine (replaces standalone comment-strategist)
• /linkedin:import analysis delegates to /linkedin:report — both consume the same trends CLI; the import flow runs the report inline instead of duplicating the analysis pipeline
• Router gating — /linkedin:monetize and /linkedin:outreach now surface "unlocks at ~1K followers" guidance so new creators are pointed at /linkedin:strategy first

Friction reduction (carried forward from prior release)

• Auto-clipboard on all content commands · max 2 interactive steps · deterministic state-updater.mjs · MCP image carousel · progressive onboarding · iCal calendar integration

---

What Is This?

This plugin gives you a complete LinkedIn thought leadership system inside Claude Code. Instead of staring at a blank 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 works.

Key capabilities:

• 360Brew profile optimization aligned with LinkedIn's AI-first content distribution (January 2026 update)
• Content Matrix System that generates 40+ post ideas from a single topic using 8 universal thought leadership angles
• Full content pipeline from ideation through post-publish 48-hour monitoring
• 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

Tip

Start with /linkedin:profile to optimize for 360Brew, then /linkedin:setup to personalize, then /linkedin:post to create your first post.

---

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-thought-leadership@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: 360Brew 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
View your stats	/linkedin:report
See all commands	/linkedin

---

Commands

All 24 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: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: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 360Brew 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	360Brew profile 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 16 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 (v2.4, 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 (v2.1, 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, v2.2)

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 (v2.1, Step 2.5) → voice-scrubber de-AI / chronicle-voice scrub (v2.2, Step 4) → fact-checker (Step 5) → editorial-reviewer craft gate run BEFORE the persona sweep (v2.4, Step 5.5) → persona-reviewer (resonance) run BEFORE lock (Step 6) → 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-thought-leadership:<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-thought-leadership	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. 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

4. 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

5. Repurpose a Viral Post

/linkedin:multiplatform
> Take my best-performing post and adapt it for a newsletter intro,
> 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 (40-50% reach suppression)
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	360Brew 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-thought-leadership.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

---

What This Plugin Does Not Cover

Area	Why	Alternative
LinkedIn API integration	No official API for content posting	Copy/paste from generated drafts
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
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, 360Brew profile 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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The algorithm rewards expertise, consistency, and authenticity. Everything else is noise.