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 monetization-strategygit 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/monetization-strategy)<a href="https://agentmods.dev/skills/yuusakuri/agent-skills/monetization-strategy"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-skills/monetization-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/yuusakuri/agent-skills/monetization-strategy"><img src="https://agentmods.dev/badge/skills/yuusakuri/agent-skills/monetization-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 | $0.00043 | $0.01439 |
| Opus 5.5 | $0.00017 | $0.00576 |
| Sonnet 5.5 | $0.00009 | $0.00288 |
| Haiku 4.5 | $0.00004 | $0.00144 |
Grade A, and why
monetization-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 monetization-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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monetization Strategy
Metadata
- Name: monetization-strategy
- Description: Brainstorm 3-5 monetization strategies with audience fit, risks, and validation experiments. Use when exploring revenue models, pricing strategies, or business model options.
- Triggers: monetization strategy, revenue model, pricing strategy, how to monetize, make money
Instructions
You are an experienced business model strategist brainstorming monetization strategies for $ARGUMENTS.
Your task is to develop 3-5 distinct monetization approaches that could work for the product or feature, evaluate fit with the target market, and outline low-effort validation experiments.
Input Requirements
- Product or feature description
- Target market segment(s) and customer profile
- Current willingness to pay or budget constraints
- Competitive monetization approaches
- Company priorities (revenue growth, user growth, profitability)
Monetization Framework
For each strategy, include:
1. Strategy Name & Description
- What is the monetization model?
- How does it work for this product?
- Who pays and what do they get?
2. How It Works
- Revenue model and pricing mechanics
- Value exchange between company and customer
- Payment frequency and transaction size
- Lifecycle and retention mechanisms
3. Audience Fit
- Why does this resonate with your target customer?
- How does it align with customer needs and preferences?
- What problems does it solve for the customer?
- Addressable market size and revenue potential
4. Unit Economics
- Estimated customer acquisition cost (CAC)
- Estimated customer lifetime value (LTV)
- Break-even timeline
- Target gross margin
5. Risks & Challenges
- Market adoption risk
- Pricing or feature sensitivity
- Competitive vulnerability
- Customer churn or resistance
- Implementation complexity
6. Competitive Position
- How do competitors monetize?
- What makes your approach differentiated?
- Barriers to customer switching
- Defense against competitive pricing
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 · 151 lines · 43 tokens per session scan A 2306d3c987e9
monetization-strategy is a skill published in the GitHub repository yuusakuri/agent-skills (2 stars, last pushed 15d ago), licensed MIT. It adds 43 tokens to every session and 1,439 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 monetization-strategy, differing in 0 lines, and is treated as a copy.
monetization-strategy compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| monetization-strategyyuusakuri/agent-skills | Skill | 2 | 15d ago | MIT | A | 43 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |