deleted: docs/tickets/an-algo/01-engagement-signal-weighting.md

deleted:    docs/tickets/an-algo/02-truth-fidelity-score.md
	deleted:    docs/tickets/an-algo/05-love-chains-referrals.md
	deleted:    docs/tickets/an-algo/06-love-letters-messaging.md
	deleted:    docs/tickets/an-algo/08-pillars-score-dashboard.md
	modified:   make_post_sell/GIT_HASH

docs/tickets/an-algo/01-engagement-signal-weighting.md

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-# Build engagement signal weighting system
-
-Implement weighted engagement scoring where different signals carry different algorithmic weight:
-
-| Signal | Weight |
-|--------|--------|
-| Purchase | 42x |
-| Share to friend | 69x |
-| Replay/re-listen | 21x |
-| Save/bookmark | 14x |
-| Positive comment | 7x |
-| Neutral comment | 1x |
-| Quick bounce (<7s) | 0x (null) |
-| Negative comment | 0x (null — algo learns nothing from hate) |
-| Report | -7x (only negative signal) |
-
-Critical: negative engagement is a NULL signal, not positive. The algorithm literally cannot optimize for outrage. Create an EngagementScore model/table to track and aggregate these weighted signals per product.

docs/tickets/an-algo/02-truth-fidelity-score.md

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-# Implement Truth Fidelity Score (7-point)
-
-Create a 7-point Truth Fidelity Score for products, computed from:
-
-1. Semantic similarity between description text and actual content
-2. Thumbnail-to-content visual coherence
-3. Title keyword overlap with content tags
-4. Buyer satisfaction rate post-purchase
-5. Refund/dispute ratio (inverted)
-6. Repeat-buyer rate from same creator
-7. Organic share rate
-
-Each scored 0-1, summed to 7 max. Creators above 4.2 get "Truth Verified" status. Store as a model field, recalculate periodically.

docs/tickets/an-algo/05-love-chains-referrals.md

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-# Implement Love Chains (single-level referral credits)
-
-When a buyer shares a product and someone else buys through that share:
-
-- Original buyer gets 7% "love commission" as store credit
-- Single-level only (NOT MLM) — no chains of chains
-- Capped at 42 referrals per product per user
-- Generate unique share links per buyer per product
-- Track referral source on purchase
-- Credit applied as store credit for future purchases
-- Dashboard for buyers to see their love chain impact

docs/tickets/an-algo/06-love-letters-messaging.md

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-# Implement Love Letters (private buyer-to-creator messages)
-
-Add private appreciation messages from buyer to creator, unlocked after purchase:
-
-- Only available to verified buyers of a product
-- Private 1-to-1, not public comments
-- Creator can optionally publish as testimonials (with buyer permission)
-- Simple message form on post-purchase page and product page (for past buyers)
-- Store in DB with buyer_id, creator_id, product_id, message, published flag
-- Creator dashboard to view and manage love letters
-- Permission toggle for buyers to allow/deny publication

docs/tickets/an-algo/08-pillars-score-dashboard.md

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-# Create creator Pillars Score analytics dashboard
-
-Real-time analytics dashboard for creators showing their four-pillar scores:
-
-- Truth Score: content-signal alignment, refund rate, repeat-buyer rate
-- Harmony Score: collaboration rate, cross-pollination, ecosystem contribution
-- Freedom Score: format diversity, audience diversity
-- Love Score: sentiment ratio, gift rate, love letter count, share rate
-
-Each pillar scored and displayed visually. Show trends over 7/14/21/42 day windows. Include "Wand Mode" preview: suggestions like "Add a 21s hook to boost discovery?" based on current metrics. Actionable insights, not vanity metrics.
-
-Blocked by: Truth Fidelity Score, engagement signal weighting, comment sentiment analysis.

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