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 yuusakuri/agent-skills --skill gtm-motionsgit clone --depth 1 https://github.com/yuusakuri/agent-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/yuusakuri/agent-skills/gtm-motions)<a href="https://agentmods.dev/skills/yuusakuri/agent-skills/gtm-motions"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-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/yuusakuri/agent-skills/gtm-motions"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-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 | $0.00058 | $0.01623 |
| Opus 5.5 | $0.00023 | $0.00649 |
| Sonnet 5.5 | $0.00012 | $0.00325 |
| Haiku 4.5 | $0.00006 | $0.00162 |
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 2mo 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.
This is a copy
100% identical to gtm-motions — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Motions
Overview
Identify and evaluate the best go-to-market motions for your product. This skill analyzes seven proven GTM approaches with specific tools and tactics to help you build a balanced acquisition strategy.
When to Use
- Selecting marketing channels for your product
- Choosing between inbound vs outbound strategy
- Building your GTM toolkit and tech stack
- Evaluating PLG vs traditional sales motion
- Planning cross-channel marketing campaigns
The 7 GTM Motions
1. Inbound Marketing
Attract customers through valuable content and thought leadership.
- Tools: LinkedIn, SEMRush, Grammarly, HubSpot, Airtable
- Tactics: Blog content, webinars, whitepapers, SEO, email nurture sequences
- Best For: B2B SaaS, technical products, long sales cycles
- Strength: Builds brand authority and attracts high-intent prospects
- Challenge: Requires consistent content creation; slower to show results
2. Outbound Sales
Proactively reach target prospects through direct engagement.
- Tools: LinkedIn Sales Navigator, ZoomInfo, Lemlist, Apollo, Hunter
- Tactics: Cold email campaigns, LinkedIn outreach, phone prospecting, personalized demos
- Best For: Enterprise sales, high-value contracts, niche markets
- Strength: Predictable pipeline generation; control over target selection
- Challenge: Low response rates; resource-intensive; requires skilled sales team
3. Paid Digital Advertising
Reach target audiences through paid channels with precision targeting.
- Tools: Google Ads, Meta Ads, LinkedIn Ads, Newswire, Retargeting platforms
- Tactics: Search ads, display advertising, social ads, video advertising, retargeting
- Best For: Products with clear target demographics, competitive keywords
- Strength: Fast results; scalable; measurable ROI; precise targeting
- Challenge: Can be expensive; requires continuous optimization; competitive
4. Community Marketing
Build engaged communities where customers help each other and spread the word.
- Tools: Slack, Reddit, Discord, Circle, Mighty Networks, WhatsApp
- Tactics: Community forums, user groups, events, mentorship, ambassador programs
- Best For: Developer products, communities of practice, loyal user bases
- Strength: Builds loyalty; organic word-of-mouth; valuable feedback; low CAC
- Challenge: Requires active moderation; time to build critical mass
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.
- 2mo ago First seen · 156 lines · 58 tokens per session scan A b26db17f9eee
gtm-motions is a skill published in the GitHub repository yuusakuri/agent-skills (2 stars, last pushed 14d ago), licensed MIT. It adds 58 tokens to every session and 1,623 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to gtm-motions, differing in 0 lines, and is treated as a copy.
gtm-motions compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gtm-motionsyuusakuri/agent-skills | Skill | 2 | 14d ago | MIT | A | 58 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |