Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add swan-gtm/gtm-skills --skill email-metrics-benchmarksgit clone --depth 1 https://github.com/swan-gtm/gtm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/swan-gtm/gtm-skills/email-metrics-benchmarks)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/email-metrics-benchmarks"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/email-metrics-benchmarks/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/email-metrics-benchmarks"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/email-metrics-benchmarks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.00940 |
| Opus 5.5 | $0.00023 | $0.00376 |
| Sonnet 5.5 | $0.00011 | $0.00188 |
| Haiku 4.5 | $0.00006 | $0.00094 |
Grade A, and why
email-metrics-benchmarks scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Email Metrics & Benchmarks
Email Metrics to Track
2X Levers (Metrics you can realistically double)
| Metric | Current Baseline | Good | Great |
|---|---|---|---|
| Cold email reply rate | 0.5-1.0% | 2-3% | 5%+ |
| Email open rate | 20-40% | 50% | 60%+ |
| Email click rate | 2-5% | 5-8% | 10%+ |
Performance by Outreach Type
| Outreach Type | Reply Rate |
|---|---|
| Cold outreach (no signal) | 6-8% |
| Signal-based outreach | 18-22% |
| Multi-signal stacked | 35-40% |
| Website visitor follow-up | 25-30% |
| Champion job change | 20-25% |
Email Structure Checklist
Opening (trigger) + Assumption + Social proof with numbers + Open-ended question
By Seniority
| Target | Max Sentences | Max Words |
|---|---|---|
| BTL (Managers, ICs) | 3-4 sentences | 90 words |
| ATL (VPs, C-Level) | 2-3 sentences | 60 words |
Deliverability Benchmarks
| Metric | Target | Warning | Critical |
|---|---|---|---|
| Bounce rate | <2% | 2-5% | >5% |
| Spam rate | <0.1% | 0.1-0.3% | >0.3% |
| Unsubscribe rate | <0.5% | 0.5-1% | >1% |
Sequence Performance
Email 1
- Highest open rate
- Sets the tone
- Most important to optimize
Email 2 (Day 3)
- 40-60% of Email 1 opens
- Different angle
- Shorter than Email 1
Email 3 (Day 14)
- New subject line
- Fresh approach
- Delegation ask effective
Email 4 (Break-up)
- Often highest reply rate
- Creates urgency
- Clean exit
Optimization Priorities
If Open Rate Low (<30%)
- Test subject lines
- Check sender reputation
- Verify deliverability
- Test send times
If Reply Rate Low (<2%)
- Improve relevance/personalization
- Shorten message
- Strengthen CTA
- Add social proof
- Test different frameworks
If Meeting Rate Low (<20% of replies)
- Qualify better in message
- Improve CTA clarity
- Reduce friction to book
- Follow up faster
Quick Diagnostics
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 147 lines · 57 tokens per session scan A b2bc83a1789d
email-metrics-benchmarks is a skill published in the GitHub repository swan-gtm/gtm-skills (220 stars, last pushed 7d ago), licensed MIT. It adds 57 tokens to every session and 940 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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