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 unixcrh/phuryn-pm-skills --skill gtm-strategygit clone --depth 1 https://github.com/unixcrh/phuryn-pm-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/unixcrh/phuryn-pm-skills/gtm-strategy)<a href="https://agentmods.dev/skills/unixcrh/phuryn-pm-skills/gtm-strategy"><img src="https://agentmods.dev/badge/skills/unixcrh/phuryn-pm-skills/gtm-strategy/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/unixcrh/phuryn-pm-skills/gtm-strategy"><img src="https://agentmods.dev/badge/skills/unixcrh/phuryn-pm-skills/gtm-strategy.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 | $0.00049 | $0.00822 |
| Opus 5.5 | $0.00020 | $0.00329 |
| Sonnet 5.5 | $0.00010 | $0.00164 |
| Haiku 4.5 | $0.00005 | $0.00082 |
Grade A, and why
gtm-strategy 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-strategy — 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Strategy
Overview
Create a comprehensive go-to-market strategy for a product launch. This skill covers marketing channels, messaging development, success metrics definition, and launch planning.
When to Use
- Planning a product launch
- Creating a GTM plan from scratch
- Defining a launch strategy for a new market
- Developing product-to-market fit strategy
- Preparing a product go-live roadmap
How It Works
Step 1: Gather Research Data
The system will help you load and analyze early research about your product and target market. Provide:
- Product description and key features
- Target market segment details
- Market research or validation data
- Competitive landscape information
- Any available customer interviews or survey data
Step 2: Define Marketing Channels
Evaluate which channels best reach your target audience:
- Digital marketing channels (paid search, social media, display)
- Content and inbound channels (blog, SEO, thought leadership)
- Sales and outbound channels (direct outreach, partnerships)
- Community and grassroots channels
- Product-led and viral channels
Step 3: Develop Messaging
Create audience-specific messaging that resonates:
- Core value proposition for target segment
- Key differentiators and competitive advantages
- Pain point validation and solution mapping
- Proof points and social proof strategies
- Channel-specific messaging variations
Step 4: Define Success Metrics
Establish measurable KPIs to track launch success:
- Awareness metrics (impressions, reach, brand recall)
- Engagement metrics (CTR, cost per engagement, time on site)
- Conversion metrics (signups, demos requested, trials started)
- Revenue metrics (MRR, customer acquisition cost, lifetime value)
- Market metrics (market share, segment penetration)
Step 5: Create Launch Plan
Build a phased launch timeline:
- Pre-launch preparation (messaging, channels, timeline)
- Launch day activities and announcements
- Post-launch momentum (content, partnerships, communities)
- Measurement and optimization cadence
- Success criteria and go/no-go decision points
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 · 95 lines · 49 tokens per session scan A fcc7c24dda6b
gtm-strategy is a skill published in the GitHub repository unixcrh/phuryn-pm-skills (2 stars, last pushed 8mo ago), licensed MIT. It adds 49 tokens to every session and 822 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-strategy, differing in 0 lines, and is treated as a copy.
gtm-strategy compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gtm-strategyunixcrh/phuryn-pm-skills | Skill | 2 | 8mo ago | MIT | A | 49 | 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 |