Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add stefanoskarakasis/Product-Marketing-Skills --skill gtm-motionsgit clone --depth 1 https://github.com/stefanoskarakasis/Product-Marketing-SkillsWrote 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/stefanoskarakasis/product-marketing-skills/gtm-motions)<a href="https://agentmods.dev/skills/stefanoskarakasis/product-marketing-skills/gtm-motions"><img src="https://agentmods.dev/badge/skills/stefanoskarakasis/product-marketing-skills/gtm-motions/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/stefanoskarakasis/product-marketing-skills/gtm-motions"><img src="https://agentmods.dev/badge/skills/stefanoskarakasis/product-marketing-skills/gtm-motions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00082 | $0.02852 |
| Opus 5.5 | $0.00033 | $0.01141 |
| Sonnet 5.5 | $0.00016 | $0.00570 |
| Haiku 4.5 | $0.00008 | $0.00285 |
Grade A, and why
gtm-motions 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Motions
Overview
Scores the 7 acquisition motions against your ICP's deal economics and forces a stack decision — one primary motion, at most one secondary, with a named rejection reason for every motion not selected. A motion mix picked because it "sounds right" is a budget guess with a launch attached to it; this skill replaces that guess with gates and scores.
Trigger
- When: Choosing which acquisition motion(s) to invest in for a launch, a segment, or a company-wide GTM model.
- Not for: Launch tier + full GTM brief →
go-to-market-strategy(this skill feeds its Channel Strategy section). Choosing the target segment →beachhead-segment, run first. Messaging within a chosen motion →positioning-messaging, run after. - Example prompts:
- "Which GTM motions should we use for this launch?"
- "Inbound vs outbound — which is right for us?"
- "Should this be PLG or sales-led?"
Inputs
- Args: Initiative/segment, ACV band, target sales-cycle length, current motion if any. Free format — Step 1 fills gaps conversationally.
- Defaults: If ACV and sales-cycle length are both unknown, block scoring and ask for a rough band first — motion fit runs on deal economics, not preference.
- Context keys:
/foundation/brain.md— optional, sharper with it. Sections 2 (ICP), 3 (Alternatives & Positioning). Without it, Step 0 asks two Quick-Brain questions./context/meta-patterns.md— optional; guardrails from prior motion decisions.- Brain contract: Reads Sections 2, 3. Writes: a Section 2 stub, only when the Quick-Brain ran and the user says yes in Step 5b. Never the motion stack.
Connectors (Optional)
| Connector | What it adds |
|---|---|
~~CRM |
Which motions closed deals |
~~email marketing |
Lifecycle motion performance |
~~marketing analytics |
Channel performance |
No connectors? Paste the material and I'll work from that. The output has the same shape. Pulled facts are drafts: each is tagged with category, tool and date, and nothing is written until you confirm.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed 5ce064a0aa11
- 21d ago Changed 616b074053b5
- 22d ago Changed · +24 lines 0abaf48d8fa8
- 27d ago Changed · +13 lines a50e6b312d16
- 1mo ago Changed · -2 lines a293f917b70d
- 1mo ago Changed · +3 lines 4a8fdf6bce93
- 2mo ago First seen · 203 lines · 82 tokens per session scan A 3cf47c87aedd
gtm-motions is a skill published in the GitHub repository stefanoskarakasis/Product-Marketing-Skills (8 stars, last pushed yesterday), licensed MIT. It adds 82 tokens to every session and 2,852 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
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