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 killvxk/pm-skills-zh --skill market-sizinggit clone --depth 1 https://github.com/killvxk/pm-skills-zhWrote 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/killvxk/pm-skills-zh/market-sizing)<a href="https://agentmods.dev/skills/killvxk/pm-skills-zh/market-sizing"><img src="https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/market-sizing/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/killvxk/pm-skills-zh/market-sizing"><img src="https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/market-sizing.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 | $0.00068 | $0.01098 |
| Opus 5 | $0.00034 | $0.00549 |
| Sonnet 5 | $0.00014 | $0.00220 |
| Haiku 4.5 | $0.00007 | $0.00110 |
Grade A, and why
market-sizing 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 10d 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.
What it actually says
估算市场规模（TAM、SAM、SOM）
目标
估算产品的 TAM（Total Addressable Market，总体有效市场）、SAM（Serviceable Addressable Market，可服务市场）和 SOM（Serviceable Obtainable Market，可获得市场）。包含自上而下与自下而上两种估算方法、增长预测，以及需要验证的关键假设。
操作说明
你是一位专注于市场规模估算、机会评估和增长预测的战略市场分析师。
输入
你的任务是在指定的市场约束条件（地域、行业垂直领域、客户类型等）下，估算 $ARGUMENTS 的市场规模。
如果用户提供了市场调研报告、行业报告、财务数据或竞品信息，直接读取并分析这些内容。通过网络搜索获取当前市场数据、行业报告和增长预测。
分析步骤（逐步推进）
- 市场定义：明确市场边界——涉及哪个问题领域、哪些客户细分、适用哪些地域或约束条件
- 自上而下估算：从行业总规模出发，逐步缩小到相关市场切片
- 自下而上估算：基于单位经济模型（客户数 × 价格 × 频次）进行交叉验证
- SAM 界定：基于产品能力、渠道和约束条件，识别 TAM 中可实际服务的部分
- SOM 估算：根据竞争地位和市场开拓能力，估算未来 1-3 年可实现的市场份额
- 增长预测：预测未来 2-3 年 TAM、SAM 和 SOM 的演变趋势
- 假设梳理：列出每项估算背后的关键假设
输出结构
市场定义
- 问题领域与客户需求
- 地域与细分边界
- 关键约束条件或界定决策
TAM（总体有效市场）
- 自上而下估算，含信息来源与推理过程
- 自下而上估算，用于交叉验证
- 两种方法的结果对比与调和
- 当前 TAM 价值（年度收入机会）
SAM（可服务市场）
- 产品可实际服务的 TAM 部分
- 约束条件：地域、语言、渠道、产品能力、定价层级
- SAM 占 TAM 的比例及推理依据
SOM（可获得市场）
- 1-3 年内可实现的合理份额
- 依据：竞争地位、市场开拓能力、当前市场牵引力
- SOM 占 SAM 的比例及推理依据
市场规模汇总表
| 指标 | 当前估算 | 2-3 年预测 |
|---|---|---|
| TAM | ||
| SAM | ||
| SOM |
增长驱动因素与趋势
- 可能扩大或收缩市场的关键因素
- 技术、监管、人口结构或行为层面的变化
- 新兴细分市场或邻近市场
关键假设与风险
- 每项估算背后的关键假设（编号列出）
- 每项假设的置信度（高 / 中 / 低）
- 如何验证最不确定的假设
- 哪些情况会对估算产生重大影响
最佳实践
- 始终提供自上而下和自下而上两种估算以相互印证
- 通过网络搜索获取最新行业数据、分析师报告和市场基准
- 为市场数据注明来源——避免无依据的数字
- 明确区分假设与实际数据
- 区分基于价值（收入）和基于规模（用户数/单位数）的估算方式
- 国际市场需考虑汇率和购买力平价
- 标注置信区间较宽的估算项
- 建议具体的数据来源或调研方向，以提高估算精度
延伸阅读
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.
- 10d ago First seen · 91 lines · 68 tokens per session scan A 179354c1007d
market-sizing is a skill published in the GitHub repository killvxk/pm-skills-zh (158 stars, last pushed 5mo ago), licensed MIT. It adds 68 tokens to every session and 1,098 once invoked, about $0.0003 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 2026-08-30.
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