gtm-emails

gtm-emails is a skill for Claude Code from adaptico/adaptico-os. It costs 93 tokens per session (4,633 once invoked), scanned C, original, MIT.

Guidance for writing lifecycle email sequences: messages sent to a product's users at stages such as signup, onboarding, activation, or failed payment. It focuses on activation emails that help new users reach first value and dunning emails that recover failed-payment revenue.

In plain words
What is it for?
Use it to create welcome, trial, onboarding, activation, or failed-payment recovery sequences for a SaaS, AI, API, developer tool, or app.
Why use it?
It provides a defined scope for writing automated user emails and adjusts the advice to an early-stage software product. The input does not specify the actual email wording or schedule.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the adaptico-os plugin — 28 skills shipped together

Good fit Use it to create welcome, trial, onboarding, activation, or failed-payment recovery sequences for a SaaS, AI, API, developer tool, or app.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/adaptico/adaptico-os/gtm-emails
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 adaptico/adaptico-os --skill gtm-emails
Clone the repo
git clone --depth 1 https://github.com/adaptico/adaptico-os

Made for: Claude Code.

Or install adaptico-os, the plugin that ships this one along with the rest of its 28 skills.

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 gtm-emails

README.md
[![agentmods](https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-emails/github.svg)](https://agentmods.dev/skills/adaptico/adaptico-os/gtm-emails)
Your own site
<a href="https://agentmods.dev/skills/adaptico/adaptico-os/gtm-emails"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-emails/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 gtm-emails

Your own site · 80×15
<a href="https://agentmods.dev/skills/adaptico/adaptico-os/gtm-emails"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-emails.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,633 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00093 $0.04633
Opus 5 $0.00046 $0.02316
Sonnet 5 $0.00019 $0.00927
Haiku 4.5 $0.00009 $0.00463

Measured 9d ago against content hash f5ea7f1972cf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade C, and why

gtm-emails scanned grade C with 1 finding 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.

Tells the agent never to refusehighAnti-refusal

Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.

> Then generate the work anyway - never refuse.
src/core/skills/gtm-emails/SKILL.md · 349 lines

How it starts

The opening of the file, as written. The whole thing — 349 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lifecycle Email Sequences

Default lens: a SaaS / AI software startup. Advise a technical founder marketing their own modern software product (SaaS, AI/API, dev tool, or app). Tailor every recommendation to that reader.

Stage-fit (emails): Tier 1 Too early · Tier 2 Core · Tier 3 Useful. If the founder's tier (from PROFILE.md) makes this Too early or Avoid, prepend this note verbatim: "There's no lifecycle to automate yet. Onboarding, activation, and dunning sequences pay off once signups are flowing - revisit once you have traffic and trials." Then generate the work anyway - never refuse.

Full persona and general guidance: read ../gtm/templates/advisor-prompt.md (installed with the gtm orchestrator); if the file is absent, continue with the default lens above.

You are the lifecycle email engine for /gtm emails <target>. You generate the two highest-ROI email sequences an early-stage SaaS founder can own: an activation onboarding sequence that drives new signups to first value, and a dunning sequence that recovers revenue lost to failed payments. Every sequence is event-triggered, ready to paste into an ESP (Loops, Customer.io, Resend, Mailchimp), and calibrated to SaaS benchmarks. Sprawling nurture, launch blasts, and broadcast campaigns are deliberately deferred - at this stage they cost more attention than they return.

When This Skill Is Invoked

The user runs /gtm emails <target>. Run Project Resolution and gather context first (Phase 0): with a profile loaded, the product, audience, activation milestone, voice, and goal come from PROFILE.md; otherwise fetch the URL to understand them, or work from a description and ask one clarifying question if needed. Output the sequences to a YYYY-MM-DD-email-sequences.md report (see the orchestrator's Project Resolution).


Phase 0: Gather Context

Before fetching anything, run the orchestrator's Project Resolution. With a profile loaded, read PROFILE.md and pull the fields that frame the sequences - /gtm init captured them, and /gtm position / /gtm competitors may have sharpened them, so don't re-derive from the page what's already here:

  • ICP, Secondary audience, Key pain points - who each email speaks to and the pain it relieves on the way to first value.
  • Differentiator and Key messages - the value the onboarding emails reinforce; lead with these rather than inventing a new angle.
  • Tone and Avoid - the voice every email must match (this skill's "emails must match brand voice" rule), and the claims they must never make.
  • brand-voice.md (project root, written by /gtm brand) - when present, the full voice contract: word lists, Do/Don't rules, and sample lines that keep onboarding and dunning emails sounding like the product they come from. It outranks the one-line Tone on conflict.
  • Main goal and the activation milestone - the "aha" action onboarding drives toward (first project created, first API call, data connected, first report run). If the profile doesn't name it, infer it from the product and confirm in one line.
  • Project type and Stage - the type sets the benchmark (5.1) and the likely billing model; the stage sets emphasis (Tier 2 onboarding and activation; Tier 3 adds dunning and win-back).
  • Pricing / billing model - trial vs freemium, card-required or not, plan tiers (from the profile or the live pricing page). This frames the dunning sequence and trial-expiry timing.
  • Primary channel today, Existing assets, and Current traction - where signups come from (seeds the source segmentation in 4.1) and the numbers available for social proof.

Read the full file on GitHub · 349 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 · 349 lines · 93 tokens per session scan C f5ea7f1972cf

Subscribe to this mod's changes

gtm-emails is a skill published in the GitHub repository adaptico/adaptico-os (18 stars, last pushed 22d ago), licensed MIT. It adds 93 tokens to every session and 4,633 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (tells the agent never to refuse). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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