ktg-plugin-marketplace/plugins/linkedin-thought-leadership/skills/linkedin-voice/SKILL.md

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linkedin-voice

LinkedIn voice training, profile optimization, content differentiation, and authenticity checking. Covers voice profile building, drift detection, 360Brew profile alignment, originality scoring, and maintaining authentic presence on LinkedIn. This skill should be used when the user wants to optimize their LinkedIn profile, train their voice, check content originality, detect voice drift, build a voice profile, or ensure their content is differentiated from commodity content. Triggers on: "optimize my LinkedIn profile", "360Brew", "profile optimization", "analyze my voice", "build voice profile", "voice audit", "does this sound like me", "voice drift", "is this original", "differentiation check", "originality check", "commodity content", "unique angle", "am I authentic", "my writing style", "train my voice", "headline optimization".

Voice and Profile Domain

This skill covers voice identity, profile optimization for the 360Brew algorithm, content differentiation, and authenticity maintenance.

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Commands

Command	Purpose	When to Use
/linkedin:profile	360Brew profile optimization	Profile setup and audit

Agents

Agent	Model	Responsibility
voice-trainer	Sonnet	Voice profile building + drift detection
differentiation-checker	Sonnet	Originality scoring + commodity detection

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360Brew Profile Validation (January 2026)

This is the most significant LinkedIn algorithm change since the platform launched.

The Fundamental Shift

Before January 2026: Post something -> Goes to 10% of your audience -> LinkedIn tracks engagement -> Decides if more people should see it.

After January 2026: LinkedIn auditions you FIRST. Before your post goes anywhere, the algorithm scans your profile to determine if you're actually qualified to talk about the topic.

The 360Brew Scoring System

LinkedIn's 150B parameter foundation model evaluates five criteria before your post reaches anyone:

Criteria	What It Checks	Impact if Missing
About Section	Does it establish expertise on this topic?	High - first signal of credibility
Experience Section	Do you have relevant background with impact statements?	High - proves you've done the work
Content History	Have you posted about this topic before?	Medium - consistency signal
Network	Are you connected to other professionals in this space?	Medium - social proof
Engagement Patterns	Do you comment on posts about this topic?	Medium - active participation

If these don't align with your post topic, your reach gets throttled. Hard.

Strategic Implications

Before you post again, audit your profile:

Ask yourself: "If LinkedIn's AI read this, would it believe I'm an expert on the topics I post about?"

If the answer is no, fix that first.

For detailed algorithm mechanics, see references/algorithm-signals-reference.md.

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Profile Optimization Checklist

About Section (CRITICAL)

Your About section is the first signal telling 360Brew what you're qualified to discuss.

Structure for optimization:

First 2-3 lines (visible without "see more"):

• Front-load your specific expertise claim
• Use domain-specific terminology
• State WHO you help with WHAT problem

Full About section:

[Specific expertise claim with domain terminology]
[WHO you help + specific RESULT you deliver]

[Your story - brief, relevant to your expertise]
[Credentials that validate your expertise]
[Frameworks/approaches you use]
[How to connect/work with you]

Experience Section (HIGH IMPACT)

Transform each role with impact statements, not task lists:

• "Deployed first Copilot Studio agent handling 40% of internal inquiries"
• "Built RAG solution processing 12,000+ feedback entries"
• "Achieved documented 968% ROI on AI initiatives"

Headline Formula

WHO you help + RESULT you deliver

Strong: "Helping public sector leaders implement AI that actually works | AI Advisor @ Statens vegvesen"

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Voice Training

Building a Voice Profile

The voice-trainer agent analyzes your writing samples to identify:

1. Sentence structure patterns -- Short/long mix, fragments, questions
2. Word choice signatures -- Technical depth, jargon level, unique phrases
3. Hook style -- How you naturally open posts
4. Storytelling approach -- How you construct narratives
5. Tone signature -- Formal/informal, humorous/serious, provocative/measured

Voice Drift Detection

Over time, content can drift from your authentic voice -- especially when using AI tools.

Warning signs:

• Posts feel "corporate" or "polished but generic"
• Comments don't match your post voice
• Engagement drops despite consistent posting
• You wouldn't say this out loud

Prevention:

• Quarterly voice audits (use voice-trainer agent)
• Read posts aloud before publishing
• Maintain voice samples in assets/voice-samples/
• Compare drafts against your voice profile

Voice Samples

Rule: Always read assets/voice-samples/ before generating content. This directory contains reference posts that represent the user's authentic voice.

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Content Differentiation

The Originality Framework

The differentiation-checker agent evaluates content across five dimensions:

1. Angle uniqueness -- Is this perspective novel?
2. Evidence quality -- Are you citing unique sources/experiences?
3. Framework originality -- Are you creating or borrowing frameworks?
4. Voice distinctiveness -- Would readers know this is you without the byline?
5. Value density -- Is every sentence earning its place?

Commodity Content Detection

Red flags for commodity content:

• Could be written by anyone in your field
• Contains only widely-known advice
• Uses the same examples everyone uses
• Lacks personal experience or data
• No contrarian or unique angle

Fix strategies:

• Add personal data/experience
• Take a contrarian position (and defend it)
• Combine two seemingly unrelated domains
• Go deeper than surface-level advice
• Share what you learned from failure, not just success

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Common Patterns

User: "Does this sound like me?"

1. Load voice profile and samples
2. Compare draft against voice signatures
3. Identify specific drift points
4. Suggest targeted edits to restore voice

User: "Is this original enough to post?"

1. Run differentiation check
2. Search for similar published content
3. Score across five dimensions
4. Suggest strategies to increase uniqueness

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Reference Files

File	When to Read
references/algorithm-signals-reference.md	Profile optimization, 360Brew
references/linkedin-visual-style.md	Visual identity consistency
assets/voice-samples/	Voice reference (always read before content creation)
config/user-profile.template.md	User personalization setup