9 improvements across 3 tracks: Onboarding: /linkedin:onboarding wizard, README Quick Start rewrite Content Quality: voice drift scoring, industry angle variants, /linkedin:carousel, /linkedin:react multi-URL comparison Analytics: automated week-rollover, day-of-week heatmap, month-over-month reports 25→27 commands. All Q2 ROADMAP items completed. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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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, output: "Voice drift: LOW CONFIDENCE (X/5 samples). Scoring based on voice profile only." and score only against the profile description (dimensions 1-2 and 4-6), skipping opening patterns (dimension 3) which needs real samples.
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.