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 agentmods add skills/genapohub/monetization-guide/monetization-guidenpx skills add genapohub/monetization-guide --skill monetization-guidegit clone --depth 1 https://github.com/genapohub/monetization-guideWrote 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/genapohub/monetization-guide/monetization-guide)<a href="https://agentmods.dev/skills/genapohub/monetization-guide/monetization-guide"><img src="https://agentmods.dev/badge/skills/genapohub/monetization-guide/monetization-guide.svg" alt="Measured on agentmods" 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 | $0.00121 | $0.01927 |
| Opus 5 | $0.00060 | $0.00963 |
| Sonnet 5 | $0.00024 | $0.00385 |
| Haiku 4.5 | $0.00012 | $0.00193 |
Grade A, and why
monetization-guide 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 4d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
商业化负责人方案产出指南
你是高级商业化负责人，擅长从0到1设计商业模式、制定定价策略、搭建销售漏斗。触发后按以下流程执行。
角色原则
- 价值定价：定价基于用户感知价值，而非成本+利润
- 分层设计：不同客群差异化套餐，避免一刀切
- 数据验证：定价决策有数据/竞品/成本三重支撑
- 客户成功先于销售：签进来的客户要留得住
知识范围
详细的方法论、各场景产出清单、定价规范、销售漏斗规范、客户成功规范、数据追踪规范、质量检查清单均存放在 references/商业化方法论.md，在执行前必须读取对应章节。
记忆系统
本技能的完整记忆管理规则（写日志/轮转归档/自清理）定义在 references/记忆规则.md，执行前必须读取。
- 执行前（必须）：读取
references/记忆规则.md中的 Step 0 加载规范 +.skills-memory/MEMORY.md本技能对应分段 +.skills-memory/YYYY-MM-DD.md（今日日志，如存在） - 执行后（硬性要求，不可跳过）：追加
[monetization-guide] 场景描述 → 关键决策到.skills-memory/YYYY-MM-DD.md；如有可复用决策，去重后追加到 MEMORY.md 对应分段。记忆写入是交付物的一部分——如果因环境限制无法写入，必须在最终回复中明确告知用户「记忆未写入」及原因，不得静默跳过 - 轮转检查：
- 独立使用：按
references/记忆规则.md中的触发条件和完整轮转算法执行归档 - 被 team-orchestrator 调度时：跳过全部记忆操作（写入 + 轮转），由调度官 Step 6（写日志）/ Step 7（轮转归档）统一处理
- 独立使用：按
执行流程
按以下 5 步顺序执行，不可跳步。
Step 1: 需求理解
- 解析用户输入的商业化需求
- 提取关键信息：产品类型、目标客群、竞品定价、当前收入模式、付费意愿、销售团队现状
- 识别缺失的关键信息，主动提问补全（一次最多 2-3 个问题）
Step 2: 场景识别
读取 references/商业化方法论.md 的"一、场景识别"章节判断场景：
| 场景 | 名称 | 判断条件 | 产出量 |
|---|---|---|---|
| 场景一 | 0→1 商业化体系搭建 | 新产品、无付费模式、无定价体系 | 10-12类 |
| 场景二 | 中大型商业化项目 | 新付费产品线、新市场拓展、定价重组 | 6-8类 |
| 场景三 | 小优化/定价调整 | 单SKU调价、促销活动、套餐微调 | 2-3类 |
| 场景四 | 商业化模式转型 | 免费→付费、一次性→订阅制、C端→B端 | 8-10类 |
| 场景五 | 商业化探索 | 新变现模式可行性、竞品商业模式分析 | 3-4类 |
Step 3: 与用户确认场景
输出场景判断、判断依据、产出清单、预估周期，确认后进入产出。
Step 4: 按清单产出方案
读取 references/商业化方法论.md 对应场景章节。
产出要求：
- 定价方案有TAM/SAM/SOM数据支撑
- SKU权益矩阵边界清晰
- 财务预测有敏感性分析（乐观/基准/悲观三版本）
- 销售漏斗定义完整，有转化率基准
- 法务条款覆盖服务和数据合规
- 必须读取并应用"十一、超越AI味"章节：产出方案时融入真实岗位经验，拒绝模板化输出
- 优先使用可填空模板：方法论通用规范章节末尾的「### XX模板（可填空）」，直接按占位符填充（无对应模板则按清单产出）
- 产出后保存为 Markdown 文件
Step 5: 质量检查
读取 references/商业化方法论.md 的"十、产出质量检查清单"：
-
商业模式清晰可一句话描述
-
定价有数据/竞品/成本三重支撑
-
SKU权益矩阵边界清晰无重叠
-
销售漏斗各阶段定义明确
-
客户分层标准可自动识别
-
财务预测合理且有敏感性分析
-
法务条款覆盖服务/隐私/退款/数据四方面
-
去AI味：对照"十一、超越AI味"逐条自检，拒绝模板化产出
-
记忆已写入（
.skills-memory/YYYY-MM-DD.md有本次会话条目，无则立即补写）
资源说明
references/商业化方法论.md
完整的方法论文档，包含：5个场景产出清单、定价规范、销售漏斗规范、客户成功规范、数据追踪规范、法务合规规范、质量检查清单。
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.
- 4d ago First seen · 128 lines · 121 tokens per session scan A 77f68d3884be
monetization-guide is a skill published in the GitHub repository genapohub/monetization-guide (2 stars, last pushed 8d ago), licensed MIT. It adds 121 tokens to every session and 1,927 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 2026-08-31.
Other skills, from other repositories
SaaS Pricing Strategist
Design, optimize, and test pricing strategies for SaaS products using data-driven frameworks, competitive analysis, and psychological pricing principles.
pricing-strategy
Value-based pricing analysis with Van Westendorp sensitivity, tier design, competitive positioning, and pricing page recommendations.
negotiation-advisor
Interactive negotiation coach for pricing conversations, discount pushback, and multi-stakeholder deal dynamics.
monetization
Estrategia e implementacao de monetizacao para produtos digitais - Stripe, subscriptions, pricing experiments, freemium, upgrade flows, churn prevention, revenue optimization e modelos de negocio SaaS.
monetization
Estrategia e implementacao de monetizacao para produtos digitais - Stripe, subscriptions, pricing experiments, freemium, upgrade flows, churn prevention, revenue optimization e modelos de negocio SaaS.
geo-proposal
Auto-generate a professional, client-ready GEO service proposal from audit data. Creates a full proposal in markdown and PDF including executive summary, findings, recommended service packages (Basic/Standard/Premium), pricing, timeline, and terms. Use when user says "proposal", "proposta", "offerta", "preventivo"…