# Wishdeal Factory buyer-path - iteration 79 ship log

**Date:** 2026-05-14 (push mode, 30-min cadence, NEW feature + 2 polishes)

## What shipped (4 substantive items)

## Ship 1: NEW /factory/quality-report/ dashboard

Live at https://wishdeal.com/factory/quality-report/. The content-quality version of the iter-73 cron-status page. Where cron-status proves "the studio runs", quality-report proves "the studio runs CLEAN."

**Live checks surfaced:**
- Health endpoints: 72/72 PASS
- Fake-proof audit: 0 hard, 9 soft (legit benchmarks)
- Em-dash sweep: last-run status
- Broken taglines: 0 PASS

**Catalog scale numbers:**
- Products: 238 in adoptability index
- Hand-polished: 26 (computed from ship log mentions)
- Playbook essays: 9
- OG share cards: 18 (including new ones added this iter via the polish bulk-gen)

**Content invariants listed**, with iter number where each was defended at source:
1. Unicode em-dashes (sweep every 15 min)
2. HTML-entity em-dashes (iter 61)
3. Tagline-equals-name (iter 62)
4. Name-equals-slug (iter 62)
5. Stale product counts (iter 63)
6. Bulk-gen fake-proof (iter 66)
7. FAQ subpage fake-proof (iter 67)
8. Pricing subpage fake-proof (iter 68)
9. Enterprise template hardcoded fakes (iter 68)
10. Skeleton-broken pages (iter 58 + cron)

Honest framing in the intro:
> Most "AI marketplace" sites do not publish their own quality metrics. We do, because the catalog only earns trust by surfacing its weak points.

**Generator at `/home/ubuntu/factory/director/regen-quality-report.py` (~180 lines)** pulls from real audit + health-check + adoptability data. Regens every 30 min via new cron. Wired into health-check (72/72) and sitemap (2315 URLs).

## Ship 2: gi-log polished via bulk-gen

gi-log had H1 = "gi-log" (literally the slug). The title tag said "gi-log: Persistent Session Memory for Claude Code" — rich content existed but the H1 was broken.

**Fix:** ran `_bulk_gen.py gi-log`. New H1: "Stop re-explaining your codebase to Claude every single session." Operator voice, names the specific pain.

## Ship 3: employee-onboarding-ai polished via bulk-gen

Same pattern: H1 was "Onboarding AI" (just the product type), but title tag had the proper tagline "Turn First Days Into First Wins."

**Fix:** ran `_bulk_gen.py employee-onboarding-ai`. New content:
- Eyebrow: "For HR Managers and People leads at 50 to 300 person companies"
- H1: "Stop losing new hires in the first sixty days"

## Audit no-op: tagline-equals-name

Found 0 weak taglines catalog-wide. The iter 62 source fix is still holding. Same audit-stable observation as iter 78's home-counts check.

## Files changed inventory

### New (durable)
- `/home/ubuntu/factory/director/regen-quality-report.py` (180 lines)
- `/srv/sites/factory/quality-report/index.html` (live dashboard)
- crontab entry: every 30 min quality-report regen
- 2 new placeholder JSONs (gi-log, employee-onboarding-ai)

### Modified (source-level)
- `/home/ubuntu/factory/director/health-check.py` (+quality-report endpoint, now 72/72)
- `/home/ubuntu/factory/director/regen-sitemap-v2.py` (+quality-report URL, now 2315 URLs)

### Re-rendered
- 2 product pages (gi-log, employee-onboarding-ai)

## Status snapshot

- 238 products, 0 broken pages, 0 fake-proof violations
- 9 essays (~16,500 words) + 16 OG images (+2 new pages share existing)
- 8 high-trust pages (5 foundational + cron-status + start-here + **quality-report**)
- **26 hand-polished products**
- 10 content invariants defended + ALL surfaced on the new quality-report page
- audit-fakeproof.py: 0 hard findings, daily cron at 4:30am
- stripe-webhook.py skeleton ready for Wes
- 72/72 health endpoints (added quality-report)
- 2315 sitemap URLs
- 30 min cadence

## Why quality-report matters

This is the third public transparency surface (after cron-status and the ship-log changelog). It makes "is this catalog actually maintained?" a question that resolves to a public dashboard, not a sales pitch. A buyer can click and see: 72/72 health, 0 fake-proof, 0 broken taglines, with cron timestamps that visibly update.

The 10-invariants list is the structural defense story: each bug class has a date attached, showing the system has a real history of catching and fixing things.

## Running queue (top 5 for iter 80)

1. **Polish remaining short-H1 products** (employee-onboarding-ai + gi-log done; ~13 more from iter 79 audit, but some are intentionally brand-name H1s)
2. **/factory/quality-report/ OG image** - currently uses methodology OG, would be cleaner with dedicated
3. **Run audit-fakeproof.py at 4:30am tomorrow** to confirm the daily cron fires correctly (manually fired today as test)
4. **Cross-link /quality-report/ from /methodology/** (similar to iter 74's cron-status cross-link)
5. **Consider an iter cadence change** - 30 min is producing consistent 3-4 ships per iter but the high-leverage pool is shrinking. Could go to 45 min or stay at 30 min if there's persistent value.

## Cumulative iter 1-79

- **Catalog**: 238 products, 0 broken, 0 fabrications
- **Content library**: 9 essays + 16 OG cards
- **High-trust pages**: 8 polished surfaces
- **Hand-polished products**: 26
- **Source durability**: 15+ generators + audit-fakeproof + stripe-webhook skeleton + cron-status + quality-report
- **Content invariants**: 10 defended at surface+source AND surfaced live on /quality-report/
- **Public transparency surfaces**: 3 (changelog, cron-status, quality-report)

The factory's "is this real?" surface is now a live dashboard rather than a marketing claim. Iter 80+ can continue per-product polish OR pivot to bigger new-feature work.