campaign-copywriting

Generates cold email campaign copy through a four-step confirmation workflow.

Updated Aug 2, 2026
One-click install
npx skills add https://github.com/Pinkycherry/newbusinessideas3 --skill campaign-copywriting-pinkycherry
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: campaign-copywriting
Source: https://github.com/Pinkycherry/newbusinessideas3/tree/main/.claude/skills/campaign-copywriting
Command: npx skills add https://github.com/Pinkycherry/newbusinessideas3 --skill campaign-copywriting-pinkycherry

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Writing cold email campaigns that get replies requires research, personalization, and disciplined structure. This Skill removes guesswork by guiding you through a stepwise confirmation process so every campaign decision is approved before final copy is produced. ## Core Features & Use Cases - Stepwise Confirmation Flow: Confirms campaign direction, subject line and first line strategy, and body structure before outputting final copy, preventing wasted drafts. - Complete Sequence Generation: Produces Email 1 variants plus threaded and new-thread follow-ups (Days 3-12) with rotated value propositions across save time, make money, and save money angles. - Machine-Readable Output: Emits a variants.yaml file matching the markdown copy exactly, ready for upload to Smartlead via the smartlead-campaign-upload-public skill. - Use Case: Given a campaign strategy document or a client website URL, produce a full 4-email cold outreach sequence with AI personalization variables like {{ai_customer_type}} and a QA-checked final draft. ## Quick Start Ask the AI to write a cold email campaign for your product using this skill and provide your website URL or campaign strategy document.

Frequently Asked Questions about campaign-copywriting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a cold email campaign that gets replies?

Start by confirming the campaign direction: target audience, pain point, value proposition, and proof point. Then choose a first line strategy (problem sniffing, whole offer, or AI personalization), keep emails to 50-90 words, and end with a low-effort CTA answerable in five words.

How to personalize cold emails at scale with AI variables?

Use AI-generated variables like {{ai_customer_type}}, {{ai_company_mission}}, and {{ai_product_type}} derived from the prospect's website or LinkedIn. Only add them when the prospect's business context changes how your product helps them; otherwise keep copy static and use situation recognition signals.

What should cold email follow-up sequences look like?

Send Email 2 on day 3-4 threaded with no subject, Email 3 on day 7-8 as a new thread, and Email 4 on day 11-12 as a redirect or resource offer. Rotate value propositions across save time, make money, and save money, and never reference previous emails.

When should I not use AI personalization in cold emails?

Skip AI company context when the use case is identical regardless of the prospect's business, such as commodity products or narrow homogeneous targeting. If the personalization would feel forced or removing it changes nothing, rely on static copy with custom research signals instead.

What words and phrases should be avoided in cold email copy?

Avoid generic openers like "I hope this email finds you well", weak value props like "We help companies", and high-pressure CTAs like "Let's hop on a call". Also avoid em dashes, the subject line "Curious", and follow-up openers that reference previous emails.