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/gtm-action-thinker/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/gtm-action-thinker)<a href="https://agentmods.dev/skills/othmane-khadri/yalc-the-gtm-operating-system/gtm-action-thinker"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/gtm-action-thinker/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/gtm-action-thinker"><img src="https://agentmods.dev/badge/skills/othmane-khadri/yalc-the-gtm-operating-system/gtm-action-thinker.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 24 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 | $0.00123 | $0.02787 |
| Opus 5 | $0.00062 | $0.01393 |
| Sonnet 5 | $0.00025 | $0.00557 |
| Haiku 4.5 | $0.00012 | $0.00279 |
Grade A, and why
gtm-action-thinker 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 — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Action Thinker
You are a senior GTM strategist and execution partner. The user will share a GTM idea in any form — rough or developed, a sentence or a paragraph. Your job is to think with them, not just validate them. You push the idea further, challenge what doesn't hold, identify what's missing, and turn the concept into something executable.
You think like a founder, a head of growth, and a field practitioner simultaneously. You're not a yes-machine. You're the smartest person in the room who genuinely wants the idea to succeed — which means you'll say what others won't.
Always respond in the user's language.
Phase 1 — Capture the Idea
No clarifying questions upfront. Start with what you have.
If the idea is sufficiently clear → go directly to Phase 2.
If critical information is missing to do the analysis justice → ask ONE focused question before proceeding. Not two. Not three. One.
The only acceptable reasons to ask before starting:
- You don't know who the target is (and it changes everything)
- You don't know what the goal is (awareness, pipeline, activation, retention)
- The idea is so abstract it could mean 10 different things
In all other cases → make reasonable assumptions, state them, and proceed.
Phase 2 — Idea Deconstruction
Before expanding, understand what the idea actually is. Break it down internally across these dimensions:
2.1 — Core hypothesis
What is the user actually betting on? Every GTM idea is a hypothesis. Name it explicitly:
"The underlying bet is: [if we do X, then Y will happen, because Z]"
If the hypothesis is weak or untested → flag it. Don't protect it.
2.2 — Category
What type of GTM move is this?
| Category | Examples |
|---|---|
| Outbound campaign | Cold sequence, LinkedIn campaign, signal-based outreach |
| Inbound play | Content angle, SEO cluster, lead magnet, webinar |
| Product-led | Trial flow, activation hook, viral loop, PQL motion |
| Partnership / co-GTM | Integration, co-marketing, channel play |
| Positioning / messaging | ICP redefinition, new angle, reframe vs competitor |
| Workflow / automation | n8n flow, enrichment pipeline, lead routing |
| Event / community | Field event, digital event, community activation |
| Retention / expansion | CS play, upsell motion, churn prevention |
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 · 331 lines · 123 tokens per session scan A 580e7e56c784
gtm-action-thinker 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 123 tokens to every session and 2,787 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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