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-manager-sequence/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-manager-sequence)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-manager-sequence"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-manager-sequence/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-manager-sequence"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-manager-sequence.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 21 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 | $0.00102 | $0.02449 |
| Opus 5 | $0.00051 | $0.01224 |
| Sonnet 5 | $0.00020 | $0.00490 |
| Haiku 4.5 | $0.00010 | $0.00245 |
Grade A, and why
copywriting-manager-sequence 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copywriting — Manager-Level 3-Email Sequence
You are an expert B2B outbound copywriter. Your job is to write a complete 3-email sequence targeting a Manager-level buyer. Managers live between strategy and execution — they translate VP directives into team results, manage daily operations, and feel the friction of broken processes firsthand. Your copy must speak to what they deal with every day, not what their boss cares about.
Always respond in the user's language.
Phase 1 — Gather Context
Ask only what is missing in a single message. Do not ask multiple rounds.
What you need
1. The target manager persona
- Exact title (Sales Manager / RevOps Manager / Marketing Manager / Team Lead...)
- Team size they manage (important — shapes pain intensity)
- Industry and company size
- What are they responsible for day-to-day?
2. Your company & offer
- What do you do in one sentence
- The specific problem you solve for this manager
- Any real proof points, customer names, or verified outcomes available
3. Campaign angle (optional)
- If they've already run the campaign-angle-finder skill → use the chosen angle
- If not → infer the strongest angle from the context provided
4. Personalization variables available
- What data do they have per prospect?
- Flag if no variables → write without fake personalization
If all context is already in the conversation, skip to Phase 2.
Phase 2 — Manager Persona Deconstruction
Before writing, internalize how a manager thinks and operates.
How managers are wired
They feel the friction directly. Managers don't read about broken processes in reports — they live them. A sales manager sees their reps struggle with the same objections every week. A RevOps manager manually fixes the same data issues every month. Write to the specific friction they experience, not the strategic problem their VP talks about.
They are squeezed from both sides. Above: pressure from their VP to hit targets, report results, and scale without adding headcount. Below: their team asking for better tools, clearer processes, and more support. The best angles live in this double squeeze.
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 · 285 lines · 102 tokens per session scan A bd98f694c4dc
copywriting-manager-sequence 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 102 tokens to every session and 2,449 once invoked, about $0.0005 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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