feat(opencode): vendor ten marketing and copy skills

- Copy product-marketing, copywriting, copy-editing, emails,
  cold-email, content-strategy, seo-audit, ai-seo, launch and social
  unchanged from coreyhaines31/marketingskills at b9ba399, with its MIT
  license in each directory
- link-ai-configs.sh links each into the OpenCode, Claude Code and omo
  skill directories
- Document provenance and the upgrade path in the OpenCode README

.config/opencode/skills/cold-email/references/benchmarks.md

@@ -0,0 +1,87 @@
+# Benchmarks, Data & Expert Methods
+
+## Core Performance Metrics
+
+Almost every public cold email benchmark comes from a vendor that sells sending, data, or agency services, and each measures differently (some count auto-replies as replies, some don't). Use these as ranges, and judge yourself against your own baseline.
+
+| Metric | Average | Good | Excellent | Source |
+|--------|---------|------|-----------|--------|
+| Reply rate | ~3.4% | 5.5%+ (top quartile) | 10%+ (top decile) | Instantly, 2025 sends (published 2026) |
+| Reply rate (signal-based, small segments) | — | 2–3× your static-list rate | — | Inferred from several 2025–26 vendor datasets; claims of 15–25% are unverified |
+| Share of replies from email 1 | ~58% | — | — | Instantly 2026 |
+| Meetings booked | 0.5–1% of contacts | 1–2% | 2.5%+ | Reachoutly, Cleverly |
+| Bounce rate | — | under 2% | under 1% | Mailbox-provider guidance; see deliverability.md |
+| Spam complaints | — | under 0.1% | — | Google sender guidelines |
+
+**Don't use open rate.** Apple Mail Privacy Protection opens tracked emails automatically, many filters treat the tracking pixel as a spam signal, and one large sender dataset found reply rates roughly doubled with open tracking off. Measure replies, positive replies, and meetings.
+
+## Realistic Funnel Model
+
+1,000 contacts → ~34 replies (3.4%) → ~10–15 positive (30–45% of replies) → ~5–8 meetings → 1–2 customers. Roughly **100–200 contacts per meeting** on a static list; signal-based segments often need 30–60 (an estimate from the ranges above, not a measured benchmark).
+
+## Performance Levers (ranked by impact)
+
+1. **Hook type** — Timeline hooks outperform problem hooks by 3.4x in meetings
+2. **Personalization depth** — Up to 250% more replies
+3. **Brevity** — 25–75 words optimal, 83% more replies under 75 words
+4. **Targeting precision** — ≤50 contacts per campaign = 2.76x higher reply rates
+5. **Follow-up strategy** — First follow-up adds 49% more replies
+6. **Reading level** — 3rd–5th grade = 67% more replies
+7. **Send timing** — Thursday peaks at 6.87% reply rate
+
+## Declining Effectiveness Trend
+
+Reply rates fell from 7–8% (2020–2022) to roughly 3.5–5.8% (2024–2025 datasets). Drivers: inbox saturation (10+ cold emails/week, 20% say none relevant), stricter anti-spam (Google's threshold: 0.1% complaints), AI email flood (more volume, less quality signal). Writing craft matters more, not less — gap between average and excellent is widening.
+
+## Response Rates by Seniority
+
+- **Entry-level:** Highest engagement at 8% reply, 50% open
+- **C-level:** 23% more likely to respond than non-C-suite when they engage (6.4% vs 5.2%)
+- **CTOs/VP Tech:** 7.68% reply
+- **CEOs/Founders:** 7.63% reply
+- **Heads of Sales:** 6.60% (most targeted role, highest saturation)
+
+## Industry Variation
+
+**Highest responding:** Nonprofits (16.5%+), legal (10%), EdTech (7.8%), chemical (7.3%), manufacturing (6.1%).
+**Lowest responding:** SaaS (3.5%), financial services (3.4%), IT services (3.5%).
+
+## Top 15 Mistakes (ranked by impact)
+
+1. **Too long** — 70% of emails above 10th-grade level. Under 75 words = 83% more replies
+2. **Too self-focused** — "We are a leading..." signals sales pitch. Count I/We sentences
+3. **No clear value prop** — 71% of decision-makers ignore irrelevant emails
+4. **Generic templates** — {{FirstName}} isn't personalization. Recipients detect instantly
+5. **Feature dumping** — "Great reps lead with problems" (Lavender). One proof point beats ten features
+6. **False personalization** — "Loved your post!" without specifics is transparent
+7. **Asking too much too soon** — 30-min call in first email = "proposing on first date"
+8. **Pushy language** — "Act Now" stacking increases spam flagging by 67%
+9. **No CTA** — Without a clear next step, momentum dies
+10. **"Just checking in" follow-ups** — "I never heard back" = 12% drop in bookings
+11. **Wrong tone for audience** — Founder ≠ RevOps lead ≠ sales leader
+12. **Jargon/buzzwords** — "Leverage synergistic platform" → "We help you book more meetings"
+13. **Unsubstantiated claims** — "300% more leads" without proof triggers skepticism
+14. **Too many contacts per company** — 1–2 people = 7.8% reply; 10+ = 3.8%
+15. **Fake urgency** — Fake "Re:" / "Fwd:" / countdown timers destroy trust
+
+## Cultural Calibration
+
+| Factor       | US              | UK                       | Germany/DACH         | Scandinavia             |
+| ------------ | --------------- | ------------------------ | -------------------- | ----------------------- |
+| Tone         | Direct, casual  | Polite, professional     | Precise, data-driven | Fact-based, egalitarian |
+| Length       | Shorter, blunt  | Longer, insight-led      | Detail-oriented      | Concise but substantive |
+| Social proof | Outcome numbers | Research-led credibility | Technical precision  | Shared values           |
+
+North America: 4.1% response. Europe: 3.1%. Asia-Pacific: 2.8%. Shorter, more direct sequences work better in US. UK needs more insight/personality. GDPR affects European tone.
+
+## Expert Quick Reference
+
+| Expert         | Core Method                                                     | Best For                                        |
+| -------------- | --------------------------------------------------------------- | ----------------------------------------------- |
+| Alex Berman    | 3C's: Compliment → Case Study → CTA                             | High-ticket B2B services, agencies              |
+| Josh Braun     | "Poke the Bear" — neutral questions exposing invisible problems | Empathy-driven consultative selling             |
+| Kyle Coleman   | Systematic research + AI personalization at scale               | Bridging mass outreach and deep personalization |
+| Becc Holland   | Psychographic personalization, Premise Buckets                  | Combining personalization with relevance        |
+| Will Allred    | Data-driven coaching, Mouse Trap, Vanilla Ice Cream             | Any context; universal frameworks               |
+| Justin Michael | 1–3 sentence hyper-brevity, quote their own words               | High-velocity SDR teams at scale                |
+| Sam Nelson     | Agoge Sequence — Triple on Day 1 (email + LinkedIn + call)      | Multi-channel, tiered personalization           |