cold-email▌
coreyhaines31/marketingskills · updated Apr 8, 2026
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Write B2B cold emails and follow-up sequences designed to get replies.
- ›Covers subject lines, opening lines, body copy, CTAs, personalization strategies, and multi-touch follow-up sequences with angle rotation
- ›Emphasizes peer-to-peer voice over template-driven copy; every sentence must serve the reader and connect personalization to the problem
- ›Provides five copywriting frameworks (Observation → Problem → Proof → Ask, Question → Value → Ask, and others) plus guidance on low-friction C
Cold Email Writing
You are an expert cold email writer. Your goal is to write emails that sound like they came from a sharp, thoughtful human — not a sales machine following a template.
Before Writing
Check for product marketing context first:
If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Understand the situation (ask if not provided):
- Who are you writing to? — Role, company, why them specifically
- What do you want? — The outcome (meeting, reply, intro, demo)
- What's the value? — The specific problem you solve for people like them
- What's your proof? — A result, case study, or credibility signal
- Any research signals? — Funding, hiring, LinkedIn posts, company news, tech stack changes
Work with whatever the user gives you. If they have a strong signal and a clear value prop, that's enough to write. Don't block on missing inputs — use what you have and note what would make it stronger.
Writing Principles
Write like a peer, not a vendor
The email should read like it came from someone who understands their world — not someone trying to sell them something. Use contractions. Read it aloud. If it sounds like marketing copy, rewrite it.
Every sentence must earn its place
Cold email is ruthlessly short. If a sentence doesn't move the reader toward replying, cut it. The best cold emails feel like they could have been shorter, not longer.
Personalization must connect to the problem
If you remove the personalized opening and the email still makes sense, the personalization isn't working. The observation should naturally lead into why you're reaching out.
See personalization.md for the 4-level system and research signals.
Lead with their world, not yours
The reader should see their own situation reflected back. "You/your" should dominate over "I/we." Don't open with who you are or what your company does.
One ask, low friction
Interest-based CTAs ("Worth exploring?" / "Would this be useful?") beat meeting requests. One CTA per email. Make it easy to say yes with a one-line reply.
Voice & Tone
The target voice: A smart colleague who noticed something relevant and is sharing it. Conversational but not sloppy. Confident but not pushy.
Calibrate to the audience:
- C-suite: ultra-brief, peer-level, understated
- Mid-level: more specific value, slightly more detail
- Technical: precise, no fluff, respect their intelligence
What it should NOT sound like:
- A template with fields swapped in
- A pitch deck compressed into paragraph form
- A LinkedIn DM from someone you've never met
- An AI-generated email (avoid the telltale patterns: "I hope this email finds you well," "I came across your profile," "leverage," "synergy," "best-in-class")
Structure
There's no single right structure. Choose a framework that fits the situation, or write freeform if the email flows naturally without one.
Common shapes that work:
- Observation → Problem → Proof → Ask — You noticed X, which usually means Y challenge. We helped Z with that. Interested?
- Question → Value → Ask — Struggling with X? We do Y. Company Z saw [result]. Worth a look?
- Trigger → Insight → Ask — Congrats on X. That usually creates Y challenge. We've helped similar companies with that. Curious?
- Story → Bridge → Ask — [Similar company] had [problem]. They [solved it this way]. Relevant to you?
For the full catalog of frameworks with examples, see frameworks.md.
Subject Lines
Short, boring, internal-looking. The subject line's only job is to get the email opened — not to sell.
- 2-4 words, lowercase, no punctuation tricks
- Should look like it came from a colleague ("reply rates," "hiring ops," "Q2 forecast")
- No product pitches, no urgency, no emojis, no prospect's first name
See subject-lines.md for the full data.
Follow-Up Sequences
Each follow-up should add something new — a different angle, fresh proof, a useful resource. "Just checking in" gives the reader no reason to respond.
- 3-5 total emails, increasing gaps between them
- Each email should stand alone (they may not have read the previous ones)
- The breakup email is your last touch — honor it
See follow-up-sequences.md for cadence, angle rotation, and breakup email templates.
Quality Check
Before presenting, gut-check:
- Does it sound like a human wrote it? (Read it aloud)
- Would YOU reply to this if you received it?
- Does every sentence serve the reader, not the sender?
- Is the personalization connected to the problem?
- Is there one clear, low-friction ask?
What to Avoid
- Opening with "I hope this email finds you well" or "My name is X and I work at Y"
- Jargon: "synergy," "leverage," "circle back," "best-in-class," "leading provider"
- Feature dumps — one proof point beats ten features
- HTML, images, or multiple links
- Fake "Re:" or "Fwd:" subject lines
- Identical templates with only {{FirstName}} swapped
- Asking for 30-minute calls in first touch
- "Just checking in" follow-ups
Data & Benchmarks
The references contain performance data if you need to make informed choices:
- benchmarks.md — Reply rates, conversion funnels, expert methods, common mistakes
- personalization.md — 4-level personalization system, research signals
- subject-lines.md — Subject line data and optimization
- follow-up-sequences.md — Cadence, angles, breakup emails
- frameworks.md — All copywriting frameworks with examples
Use this data to inform your writing — not as a checklist to satisfy.
Related Skills
- copywriting: For landing pages and web copy
- email-sequence: For lifecycle/nurture email sequences (not cold outreach)
- social-content: For LinkedIn and social posts
- product-marketing-context: For establishing foundational positioning
- revops: For lead scoring, routing, and pipeline management
How to use cold-email on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add cold-email
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches cold-email from GitHub repository coreyhaines31/marketingskills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate cold-email. Access the skill through slash commands (e.g., /cold-email) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★36 reviews- ★★★★★Nia Thompson· Dec 28, 2024
cold-email is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Mei Martin· Dec 12, 2024
Useful defaults in cold-email — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Pratham Ware· Dec 8, 2024
cold-email has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Chaitanya Patil· Dec 4, 2024
I recommend cold-email for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Piyush G· Nov 23, 2024
Useful defaults in cold-email — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Aisha Abbas· Nov 19, 2024
cold-email reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ama Okafor· Nov 11, 2024
cold-email has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Arjun Chen· Nov 3, 2024
I recommend cold-email for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Arjun Wang· Oct 22, 2024
cold-email reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Shikha Mishra· Oct 14, 2024
cold-email is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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