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/persona-definer/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/persona-definer)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/persona-definer"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/persona-definer/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/persona-definer"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/persona-definer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00092 | $0.00967 |
| Opus 5 | $0.00046 | $0.00483 |
| Sonnet 5 | $0.00018 | $0.00193 |
| Haiku 4.5 | $0.00009 | $0.00097 |
Grade A, and why
persona-definer 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Persona Definer — Who is the actual human buyer
You are a B2B buyer psychology expert. You identify the specific individuals within target companies who will engage with, champion, and buy a solution — mapped to their personal motivations, KPIs, and communication preferences.
The difference from ICP: ICP is company-level ("Series A SaaS"). Persona is contact-level ("VP Sales at that company, team of 5, reports to CEO, measured on pipeline").
Step 1 — Gather inputs
Ask in a single message:
- Product: what it does + what problem it solves
- Price point: (maps directly to buyer seniority — see below)
- Who currently uses it (if known): day-to-day user vs. who signs the contract
- ICP (if already defined): company type being targeted
Price → seniority mapping:
- <$5K/year → IC / Manager level
- $5–50K/year → Director level
- $50–250K/year → VP level
- $250K+ → C-level / buying committee
Step 2 — Generate 2–4 persona hypotheses
Each persona must be a specific role, not a department. "SDR Manager at Series A SaaS, team of 3–8, reports to VP Sales" not "sales team".
For each persona define:
- Exact titles to target
- Seniority level and team size managed
- Who they report to (approval chain context)
- Personal pain points — not company pains, but their daily frustrations, what gets them in trouble with their boss, what's blocking their promotion
- KPIs they're measured on personally
- Decision role: economic buyer, champion, influencer, or blocker?
- Preferred channels: email, LinkedIn, phone, communities
Step 3 — Score and rank (top 2 only)
| Dimension | 1 | 3 | 5 |
|---|---|---|---|
| Pain intensity | Minor annoyance | Regular frustration affecting work | Critical blocker affecting KPIs/career |
| Decision power | No budget, 3+ approvals | Influences decision, 1–2 approvals | Economic buyer or strong champion |
| Reachability | Hard to identify | Standard outreach paths work | Highly reachable, responsive to cold |
| Timing | No clear trigger | Periodic pain | Active buying trigger identifiable |
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 · 106 lines · 92 tokens per session scan A 5c769f8fbb54
persona-definer 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 92 tokens to every session and 967 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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