ktg-plugin-marketplace/plugins/linkedin-thought-leadership/assets
Kjell Tore Guttormsen 5be9c8e47c feat(ultraplan-local): v1.6.0 — /ultraresearch-local deep research command
Add /ultraresearch-local for structured research combining local codebase
analysis with external knowledge via parallel agent swarms. Produces research
briefs with triangulation, confidence ratings, and source quality assessment.

New command: /ultraresearch-local with modes --quick, --local, --external, --fg.
New agents: research-orchestrator (opus), docs-researcher, community-researcher,
security-researcher, contrarian-researcher, gemini-bridge (all sonnet).
New template: research-brief-template.md.

Integration: --research flag in /ultraplan-local accepts pre-built research
briefs (up to 3), enriches the interview and exploration phases. Planning
orchestrator cross-references brief findings during synthesis.

Design principle: Context Engineering — right information to right agent at
right time. Research briefs are structured artifacts in the pipeline:
ultraresearch → brief → ultraplan --research → plan → ultraexecute.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-08 08:58:35 +02:00
..
analytics feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00
audience-insights feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00
case-studies feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00
checklists feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00
drafts feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00
examples feat(linkedin-thought-leadership): v1.1.0 — Q2 2026 feature release 2026-04-08 06:16:35 +02:00
frameworks feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00
plans feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00
templates feat(ultraplan-local): v1.6.0 — /ultraresearch-local deep research command 2026-04-08 08:58:35 +02:00
voice-samples feat(linkedin-thought-leadership): v1.1.0 — Q2 2026 feature release 2026-04-08 06:16:35 +02:00
quick-post-resources.md feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00
README.md feat(linkedin-thought-leadership): v1.0.0 — initial open-source import 2026-04-07 22:09:03 +02:00

Personal LinkedIn Assets

This folder contains YOUR personalized content, frameworks, and insights that make this skill uniquely valuable to you.

How Assets Are Used

When you ask Claude to create content, it will:

  1. Check your PERSONALIZATION SETTINGS in SKILL.md
  2. Reference relevant assets from these folders
  3. Blend your authentic voice/examples with LinkedIn best practices
  4. Generate content that sounds like YOU, optimized for the algorithm

Folder Structure

/examples/

Store your best-performing posts for pattern analysis. Claude will study these to understand what works for YOUR audience and replicate those patterns in new content.

/templates/

Your custom post templates. When you develop a structure that works consistently, save it here so Claude can apply it to new content.

/frameworks/

Your proprietary frameworks, models, and methodologies. When creating content, Claude will reference YOUR frameworks instead of generic ones.

/case-studies/

Real examples from your work. Claude uses these for credibility and specificity instead of making up generic scenarios.

/research/

Industry research, data, and trends specific to your domain. Helps Claude create data-driven posts with current, relevant information.

/voice-samples/

Examples of your authentic writing from various contexts. Claude analyzes these to match your natural voice and style.

/audience-insights/

Your analytics, demographics, and engagement patterns. Claude uses this to optimize content for YOUR specific audience, not generic best practices.

/competitors/

Analysis of peers and influencers in your space. Helps identify content gaps and opportunities for differentiation.

Maintenance Schedule

Weekly (5 minutes)

  • Add your best post from the week to /examples/
  • Update posting time insights in /audience-insights/engagement-patterns.md

Monthly (15 minutes)

  • Analyze patterns in /examples/ and document learnings
  • Update demographics in /audience-insights/ based on LinkedIn analytics
  • Add any new frameworks developed to /frameworks/

Quarterly (30 minutes)

  • Refresh industry data in /research/
  • Update competitor analysis in /competitors/
  • Review and refine voice samples in /voice-samples/

Priority Hierarchy

If there's a conflict between:

  • Generic best practices (in /references/)
  • Your personal patterns (in /assets/)

→ Claude will prioritize YOUR patterns (with optimization suggestions if needed)

Exception: If your patterns actively harm algorithmic reach (external links, engagement bait), Claude will flag this and suggest alignment with platform mechanics while maintaining your authentic voice.

Getting Started

  1. Week 1: Fill in PERSONALIZATION SETTINGS in SKILL.md (15 minutes)
  2. Week 2-4: Add 2-3 voice samples to /voice-samples/ (20 minutes)
  3. Month 2: Start populating /examples/ with your successful posts (ongoing)
  4. Month 3: Add frameworks and case studies as they develop (ongoing)

The more you populate these folders, the more personalized and valuable this skill becomes. Think of it as a system that learns YOUR patterns over time.