sales-email-sequences

sales-email-sequences is a skill for Claude Code, Codex from seb1n/awesome-ai-agent-skills. It costs 55 tokens per session (1,878 once invoked), scanned A, original, MIT.

A plan for a series of outbound sales emails sent to potential customers over time. It covers the message for each contact, personalization, follow-ups, and when each email should be sent.

In plain words
What is it for?
Use it to create prospecting campaigns with opening emails, follow-ups, value-sharing messages, breakup emails, subject-line options, and sending schedules.
Why use it?
It replaces improvised follow-ups with a coordinated outreach process for starting conversations or re-engaging prospects.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create prospecting campaigns with opening emails, follow-ups, value-sharing messages, breakup emails, subject-line options, and sending schedules.

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Install with agentmods
npx agentmods add skills/seb1n/awesome-ai-agent-skills/sales-email-sequences
Install

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.

Any agent
npx skills add seb1n/awesome-ai-agent-skills --skill sales-email-sequences
Clone the repo
git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for sales-email-sequences

README.md
[![agentmods](https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/sales-email-sequences/github.svg)](https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/sales-email-sequences)
Your own site
<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/sales-email-sequences"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/sales-email-sequences/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.

agentmods 80×15 button for sales-email-sequences

Your own site · 80×15
<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/sales-email-sequences"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/sales-email-sequences.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,878 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.01878
Opus 5 $0.00028 $0.00939
Sonnet 5 $0.00011 $0.00376
Haiku 4.5 $0.00006 $0.00188

Measured 9d ago against content hash 4078c3967100, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

sales-email-sequences 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 9d 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.

sales/sales-email-sequences/SKILL.md · 184 lines

How it starts

The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sales Email Sequences

Design end-to-end outbound email sequences that move prospects from cold outreach to booked meetings. This skill builds persona-targeted messaging across multiple touches — intros, follow-ups, value-adds, and breakup emails — with personalization tokens, subject line variants, and send-timing cadences optimized for reply rates.

Workflow

  1. Define ICP and Persona — Establish the ideal customer profile (industry, company size, revenue range, geography) and the target persona (title, seniority, responsibilities, pain points). This determines tone, vocabulary, value framing, and which proof points resonate.

  2. Craft the Core Value Proposition — Distill your product's relevance to this persona into a single compelling statement. Focus on a specific, measurable outcome (e.g., "reduce month-end close from 10 days to 3") rather than feature lists. This value prop threads through every email in the sequence.

  3. Write the Email Sequence — Build a multi-touch sequence: an opening email that earns attention with a relevant hook, follow-ups that introduce new angles or proof points, a value-add email offering a resource, and a breakup email that creates urgency through finality. Each email should be 50–120 words in the body.

  4. Add Personalization Tokens — Insert dynamic fields for prospect name, company, industry, recent trigger events (funding rounds, job changes, earnings calls), and any known tech stack details. Personalization beyond {{first_name}} dramatically lifts reply rates.

  5. Set Timing and Cadence — Define send days, times, and intervals between touches. B2B sequences typically perform best with Tuesday–Thursday sends between 8–10 AM local time, with 2–4 day gaps between early touches and longer gaps (5–7 days) before the breakup.

Usage

Specify the target persona, your product/service, the core pain point you solve, and desired sequence length. Optionally include trigger events or specific personalization data.

Read the full file on GitHub · 184 lines

Changes

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.

  1. 9d ago First seen · 184 lines · 55 tokens per session scan A 4078c3967100

Subscribe to this mod's changes

sales-email-sequences is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 1,878 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 2026-09-03.

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