LinkedIn Hub
☀️ Today
☀️ Today — your daily orchestrator
Pick a news/event → turn it into an operator take in Composer. Every morning at 06:00 Asia/Ho_Chi_Minh the system fetches 14 DTC subscription news sources, scans them with a research model (anchored 0/2/4/6/8/10 relevance scale for $1M–$8M Shopify subscription brands), and surfaces the top 5 here + sends to Telegram. Click Use as seed on any item to open Composer with the news pre-loaded; click ⟳ Refresh digest to fetch fresh news on demand.
Trending Now
No digest yet — click Refresh to fetch news
Quick Actions Open Composer with format pre-selected
Performance Snapshot
Yesterday: — saves, — views, — DMs  📊 See Analytics →  📅 See Calendar →
Publishing Streak
Days in a row published
Post + mark published in Library
to start your streak.
✍️ Composer
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How this works
Pick what you are starting from, paste the concrete angle or proof, preview the draft plan, then generate.
1. Starting point 2. Draft plan 3. Generate + tighten
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Format — what are you creating?
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Starting point — what do you already have?
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Brief + Plan — paste the brief, preview your plan, generate
Brief formula: topic + audience + frame + specific claim or metric + what to avoid. Example: “Make a carousel for Shopify subscription operators about Recharge acquiring Skio. Frame: Audit Map. Angle: platform dependency is now a rebill / dunning / portal / data-ownership risk, not a SaaS news item. Avoid generic M&A commentary.”
Brief Paste messy notes. Specific beats polished.
Use an example
Advanced options
Pillar is optional. Use it only when you want the generator to stay inside one strategic bucket.
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Generate + Edit — attach an image or skip
📁 Drag & drop or click to upload (multiple OK)
PNG / JPG / WebP / GIF · max 10 MB each
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Preview + Save — final review
0 chars Sweet spot: 1300–1900
⚠ Text changed — recompute Voice score / Hook variants
Before saving: check the hook, remove generic claims, shorten overflowing carousel headlines, then run Score voice. For carousels, open the debug trace if the score feels weak.
Click "Score voice ▶" to analyse the draft.
Click "Get hook variants ▶" to see 5 alternatives.
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📊 Analytics

Performance across published LinkedIn posts. KPIs + per-post table + pillar aggregates + hook A/B + format breakdown. Engagement funnel (impressions → DMs) activates once comment + DM thread tracking is wired up.

📚 Library
🎙️ Voice Document — the writing rules Composer must follow
This is not the topic knowledge base. It is the voice layer: how Alex writes, what he never says, which proof patterns he trusts, and what operator language sounds natural. Sonnet turns your raw notes into a structured Voice Document. The active version is then mixed into Composer prompts so posts, carousels, comments, and scores can judge against the same style rules.
1 · Purpose
What this controls
Sentence rhythm, hooks, banned phrases, CTA style, proof standards, and vocabulary by pillar.
2 · Input
What you paste
A raw writeup: cases, frameworks, contrarian takes, signature phrases, and words you hate.
3 · Build
What AI does
Converts your notes into machine-readable JSON. Every build creates a new version; only one is active.
4 · Safety
How to rollback
If a new version writes worse, activate an older one from Version History. No content is deleted.

What to fill in

  • Anchor frame: who you are, who you serve, and what you have earned the right to say.
  • Real cases: anonymized brand size, vertical, symptom, diagnosis, intervention, result.
  • Named frameworks: reusable lenses like Month 2 Cliff or Involuntary Churn Recovery Map.
  • Contrarian takes: what most operators believe, what you believe instead, and why.
  • Signature phrases: phrases you actually use and phrases that should be banned.
  • Pillar vocabulary: how you talk about payments, retention, traffic quality, offers, refunds, etc.
  • Anchor stats: numbers or thresholds you would defend publicly or use in audits.
  • Voice laws: hard rules such as no soft CTA, no generic SaaS language, no fake certainty.
Good input shape: Brand descriptor: $3M supplements brand on Recharge. Symptom: founder thought email retention was weak. Diagnosis: M2 churn was mostly failed payments and cadence mismatch. Intervention: changed dunning timing, rebill reminders, and subscription cadence. Result: recovered X% of failed rebills over Y weeks. Teachable bit: this was billing ops, not lifecycle copy.

New Voice Document Version

Paste a full writeup below. Short notes work for a bootstrap version, but a strong version needs real material: 5-8 anonymized cases, 3-5 frameworks, banned phrases, and concrete operator vocabulary. Expect 60-120 minutes for a serious version.

Active Voice Document

No active version yet. Build one above.

Version History

VersionCreatedStatusNotes
No versions yet
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✏️ Edit
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