Cold Email

Cold Email Writing

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/cold-email from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

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.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Before Writing, Voice & Tone, Structure, Subject Lines, Follow-Up Sequences, Quality Check.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Use when writing outbound prospecting emails or cold follow-up sequences.
• Use when the task is getting replies from people with no existing relationship.
• Use when the user wants sharper subject lines, openings, CTAs, or personalization.
• Use when the request clearly matches the imported source intent: Write B2B cold emails and follow-up sequences that earn replies. Use when creating outbound prospecting emails, SDR outreach, personalized opening lines, subject lines, CTAs, and multi-touch follow-up sequences.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: 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):

1. Who are you writing to? — Role, company, why them specifically
2. What do you want? — The outcome (meeting, reply, intro, demo)
3. What's the value? — The specific problem you solve for people like them
4. What's your proof? — A result, case study, or credibility signal
5. 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.

Examples

Example 1: Ask for the upstream workflow directly

Use @cold-email to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @cold-email against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @cold-email for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @cold-email using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• 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.

• 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.

Imported Operating Notes

Imported: 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.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/cold-email, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

• benchmarks.md
• follow-up-sequences.md
• frameworks.md
• personalization.md
• evals.json
• benchmarks.md

Imported Reference Notes

Imported: 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")

Imported: 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.

Imported: 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.

Imported: 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.

Imported: 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?

Imported: 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

Imported: 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.

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.