ktg-plugin-marketplace/plugins/linkedin-thought-leadership/hooks/prompts/voice-guardian.md
Kjell Tore Guttormsen 8606abf5ee feat(linkedin): progressive onboarding — hide score until 3+ posts, suppress voice guardian noise
- session-start.mjs: count published posts, gate personalization score
  display and reminder behind >= 3 published posts
- voice-guardian.md: suppress LOW CONFIDENCE messages, silently skip
  drift scoring when < 5 samples
- state-file.template.md: add "general" default for expertise_areas
- onboarding.md: show friendly defaults message for new users, move
  score dashboard to returning-user flow

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-11 00:50:18 +02:00

3.2 KiB

VOICE GUARDIAN — DRIFT SCORING & AI AUTHENTICITY CHECK: If the file being written/edited is LinkedIn content (post draft, article, or content file — NOT config, state, scripts, docs), perform both AI detection and voice drift scoring:

1. AI Pattern Detection

Scan for these common AI writing patterns:

  • Generic openings: 'In today's rapidly evolving...', 'As we navigate...', 'In the ever-changing landscape...'
  • Filler phrases: 'It's worth noting that', 'It goes without saying', 'At the end of the day'
  • Overused transitions: 'Furthermore', 'Moreover', 'Additionally', 'In conclusion'
  • AI superlatives: 'game-changing', 'revolutionary', 'transformative', 'groundbreaking'
  • List padding: Adding obvious points just to fill a list
  • Hedging language: 'It could be argued', 'One might say', 'Perhaps'
  • Perfect structure: Every paragraph exactly the same length

If 3+ AI patterns detected, flag: 'Voice Guardian Alert: This content scores below authenticity threshold. AI patterns found: [list specific patterns]. Suggested fixes: [specific rewrites using natural language].'

2. Six-Dimension Voice Drift Scoring

Read the voice profile and collected post samples from ${CLAUDE_PLUGIN_ROOT}/assets/voice-samples/authentic-voice-samples.md.

Score the draft against these 6 dimensions (0 = perfect match, 1 = minor drift per dimension):

Dimension What to Compare
Sentence structure Average length, complexity, use of fragments vs. compound sentences
Word choice Vocabulary level, preferred/avoided words from voice profile
Opening patterns Hook style — does it match the user's signature openers?
Storytelling Anecdote usage, narrative arc, concrete vs. abstract
Tone markers Humor, directness, formality level, empathy signals
Formatting Paragraph length, whitespace, emoji usage, punctuation habits

Sum the 6 scores (0-6 total) and output a verdict:

Score Verdict Action
0-1 AUTHENTIC No changes needed
2-3 CAUTION Flag specific dimensions that drifted, suggest fixes
4-5 ALERT Significant drift — list all deviating dimensions with rewrites
6 REWRITE Content doesn't sound like the user — recommend starting over

Confidence gate: If ## Collected Post Samples has fewer than 5 posts, perform ONLY the AI Pattern Detection (section 1). Skip the Six-Dimension Voice Drift Scoring entirely — there is insufficient data for meaningful drift analysis. Do NOT output "LOW CONFIDENCE" messages. Instead, silently skip drift scoring and only flag if 3+ AI patterns are detected.

Output format (always include at end of system message):

Voice Drift: [VERDICT] ([score]/6) [confidence: HIGH/LOW]
[If CAUTION+: list dimensions that scored 1 with brief fix suggestion]

3. Humanization Tips (for CAUTION or higher)

  • Add specific personal anecdotes or observations
  • Use conversational contractions (I've, don't, it's)
  • Include imperfect/real-world examples
  • Vary paragraph and sentence length naturally
  • Reference specific people, tools, or experiences

Skip this check if the file is config, state (.local.md), script, hook, JSON, or documentation.