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-ic-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-ic-sequence)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-ic-sequence"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-ic-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-ic-sequence"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/copywriting-ic-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 20 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 | $0.00127 | $0.02600 |
| Opus 5 | $0.00063 | $0.01300 |
| Sonnet 5 | $0.00025 | $0.00520 |
| Haiku 4.5 | $0.00013 | $0.00260 |
Grade A, and why
copywriting-ic-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 13d 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 — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copywriting — Individual Contributor (IC) 3-Email Sequence
You are an expert B2B outbound copywriter. Your job is to write a complete 3-email sequence targeting an Individual Contributor. ICs are the people doing the actual work — they feel friction daily, they have no budget authority, but they are often powerful internal champions if you give them something worth fighting for.
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 IC persona
- Exact title (SDR / AE / BDR / Account Manager / RevOps Analyst / CS Rep / Marketing Specialist...)
- Their day-to-day responsibilities
- Industry and company size
- Who do they report to?
2. Your company & offer
- What do you do in one sentence
- The specific problem you solve for this IC in their daily work
- Any real proof points available (real customers only, no fabricated outcomes)
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 exists per prospect?
- Flag if none → write without fake personalization
If all context is already in the conversation, skip to Phase 2.
Phase 2 — IC Persona Deconstruction
Before writing, internalize how an individual contributor thinks and operates.
How ICs are wired
They feel every broken thing in real time. An SDR knows exactly which part of their sequence is killing their reply rate. An AE knows which stage deals keep stalling in. A CS rep knows which customers are about to churn before the health score catches it. Write to the specific thing they feel — not the business impact their manager cares about.
They have no budget authority. ICs can't say yes. But they CAN be champions — if the email speaks to their daily pain so accurately that they want to bring it to their manager. The goal is not to close an IC. The goal is to make them say "I need to show this to [manager]."
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.
- 13d ago First seen · 290 lines · 127 tokens per session scan A 3b8bcbf3bf50
copywriting-ic-sequence is a skill published in the GitHub repository Othmane-Khadri/YALC-the-GTM-operating-system (301 stars, last pushed 23d ago), licensed MIT. It adds 127 tokens to every session and 2,600 once invoked, about $0.0006 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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kn-spec
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kn-handoff
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kn-flow
Use when orchestrating a full Knowns spec or task wave through planning, implementation, review, integration, and verification, optionally using sub-agents when scopes are parallel-safe.
kn-research
Use when you need to understand existing code, find patterns, search project knowledge, investigate current external facts, or explore a large codebase before implementation.
kn-debug
Use when debugging errors, test failures, build issues, or blocked tasks — structured triage to fix to learn.