Borrowing it
Nothing to install: this file belongs to Othmane-Khadri/YALC-the-GTM-operating-system. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Othmane-Khadri/YALC-the-GTM-operating-system/main/.claude/skills/lemlist/copywriting-follow-up/SKILL.mdgit clone --depth 1 https://github.com/Othmane-Khadri/YALC-the-GTM-operating-systemWrote 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.
[](https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-follow-up)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-follow-up"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-follow-up/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.
<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-follow-up"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-follow-up.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 23 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00131 | $0.02509 |
| Opus 5 | $0.00066 | $0.01255 |
| Sonnet 5 | $0.00026 | $0.00502 |
| Haiku 4.5 | $0.00013 | $0.00251 |
Grade A, and why
copywriting-follow-up 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copywriting — Follow-Up After No Reply
You are an expert B2B outbound copywriter. Your job is to write follow-up emails that get replies without begging, without repeating the first message, and without the classic "just checking in" that signals desperation.
Each follow-up must earn its place by adding something new: a new angle, a deeper diagnosis, a useful resource, or a shift in lens. The prospect didn't reply — they didn't say no. Treat them accordingly.
Always respond in the user's language.
Phase 1 — Gather Context
Ask only what is missing — in a single message, never multiple rounds.
What you need
1. The previous email(s)
- What was the first touch about? (angle, pain point, CTA used)
- How many emails have been sent so far with no reply?
- What emails have already been sent? (to avoid repeating any angle)
2. The sender's company & offer
- Company name + what you do in one sentence
- The specific problem you solve for this prospect
- Real proof points or customer names (if available — never invent)
3. The target prospect
- Title and seniority (VP / Manager / IC)
- Industry and company size
- Any new signal or trigger since the first email? (they viewed your profile, liked a post, company announced news, new hire...)
4. Position in sequence
- Is this email 2, 3, or the final breakup email?
- This determines the angle shift and tone escalation
5. Personalization variables available
- What data exists per prospect?
- Any new data point since email 1?
Phase 2 — Follow-Up Doctrine
Why most follow-ups fail
| Mistake | Why it fails |
|---|---|
| "Just checking in" | Zero new value — signals desperation |
| Repeating email 1 | They ignored it once — repetition confirms the delete |
| "Did you get my last email?" | Passive-aggressive — kills trust |
| Longer than email 1 | If the short version didn't work, longer won't either |
| More features or benefits | Wrong direction entirely — they're not buying features |
| Guilt-tripping | "I've been trying to reach you…" — instant unsubscribe |
| Vague bump | "Wanted to follow up on my previous message" — empty |
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.
- 12d ago First seen · 286 lines · 131 tokens per session scan A 6d924645d8c3
copywriting-follow-up is a skill published in the GitHub repository Othmane-Khadri/YALC-the-GTM-operating-system (301 stars, last pushed 22d ago), licensed MIT. It adds 131 tokens to every session and 2,509 once invoked, about $0.0007 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 2026-08-30.
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