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 OneWave-AI/claude-skills --skill cold-email-sequence-generatorgit clone --depth 1 https://github.com/OneWave-AI/claude-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/onewave-ai/claude-skills/cold-email-sequence-generator)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/cold-email-sequence-generator"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/cold-email-sequence-generator/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/onewave-ai/claude-skills/cold-email-sequence-generator"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/cold-email-sequence-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00059 | $0.00734 |
| Opus 5 | $0.00030 | $0.00367 |
| Sonnet 5 | $0.00012 | $0.00147 |
| Haiku 4.5 | $0.00006 | $0.00073 |
Grade A, and why
cold-email-sequence-generator 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 12d 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Email Sequence Generator
Craft personalized, value-driven cold email sequences with optimal timing, A/B-tested subject lines, and integrated social proof. The goal of cold email is to start a conversation, not to close the sale in the inbox.
Contents
- references/email-templates.md — Per-position email templates (Emails 1-7), bodies, variables, and social-proof frameworks.
- references/output-format.md — Delivery structure, flow-and-timing table, sending best practices.
- references/optimization.md — A/B testing, performance benchmarks, segmentation, pro tips, setup checklist.
- references/quick-start-templates.md — Vertical-specific subject-line skeletons (SaaS, agency, partnership).
Workflow
- Confirm the target audience (ICP) and the core value proposition with the user.
- Select the sequence type: Classic Cold Outreach (7 emails / 2 weeks), Fast-Track (5 emails / 1 week), Long-Play Nurture (12-14 emails / 4-6 weeks), Event/Trigger-Based (3-5 emails), or Re-Engagement (5 emails).
- Select the personalization level: Hyper-Personal (unique research per prospect), Account-Based (company-specific), Segment-Based (industry/role), or Volume (template with merge tags).
- Identify the key pain points and the strongest social proof (case studies, stats, named customers) to support the campaign.
- Build the sequence using the per-position templates in references/email-templates.md. Vary the angle across emails: Introduction, Value Proof, Different Angle, Social Proof, Resource Share, Direct Ask, Breakup.
- Generate A/B subject-line variations and assign send timing per email, following references/output-format.md.
- Add personalization guidance, performance benchmarks, and optimization recommendations from references/optimization.md.
- Assemble the final deliverable in the structure defined in references/output-format.md.
Core Rules
- Always personalize the first line with something specific about the prospect or their company.
- Keep emails short; the best cold emails run under 100 words.
- Use one ask per email; never bury multiple CTAs.
- Honor replies immediately when a prospect says no or asks to stop.
- Run an A/B test on some variable in every campaign.
- Invest in follow-up: roughly 80% of responses come from emails 3-7.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 48 lines · 59 tokens per session scan A 36e68a2a13d5
cold-email-sequence-generator is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 734 once invoked, about $0.0003 per session on Opus 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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