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Agent Skill · 研究检索

tam-sam-som-calculator(谭三颂计算器)

tam-sam-som-calculator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

tam-sam-som-calculator 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 7,459。

总安装 18,927周安装 813GitHub Stars 3,871下载 6,634核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:tam-sam-som-calculator(谭三颂计算器)
来源仓库:https://github.com/deanpeters/product-manager-skills
仓库路径:skills/tam-sam-som-calculator
安装命令:
npx skills add https://github.com/deanpeters/product-manager-skills --skill tam-sam-som-calculator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/deanpeters/product-manager-skills --skill tam-sam-som-calculator

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

TAM、SAM 和 SOM 的结构化市场规模框架,具有自适应问题和引用支持的估计。

指导产品经理回答四个适应性问题,涵盖问题空间、地理位置、行业细分和目标客户,以建立可靠的市场规模估计 利用基于人口普查局、IBISWorld、Statista 和类似来源的人口估计、行业数据源和逐年预测生成受引文支持的 TAM/SAM/SOM 分析 包括可选的确定性计算器脚本,用于根据人口和 ARPU 输入计算市场规模,以及压力测试假设的验证问题 强调常见陷阱(无来源的 TAM 声明、不切实际的 SOM 捕获率、忽略 GTM 限制)并强调随着市场的发展进行年度重新评估

来源仓库内路径:skills/tam-sam-som-calculator

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/deanpeters/product-manager-skills --skill tam-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

tam-sam-som-calculator 怎么安装?

在终端执行 npx skills add https://github.com/deanpeters/product-manager-skills --skill tam-sam-som-ca…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

tam-sam-som-calculator 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

tam-sam-som-calculator 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

tam-sam-som-calculator 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

tam-sam-som-calculator 用的人多吗?

公开数据是累计安装 18,927 次,近一周安装 813 次,下载 6,634 次,GitHub 3,871 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

tam-sam-som-calculator 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 3,871 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
tam-sam-som-calculator

谭三颂计算器 · 本页

18,9273,871需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Purpose

Guide product managers through calculating Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) for a product idea by asking adaptive, contextually relevant questions. Use this to build defensible market size estimates backed by real-world citations, economic projections, and population data—essential for pitching to investors, securing budget, or validating product-market fit.

This is not a back-of-napkin guess—it's a structured, citation-backed analysis that withstands scrutiny.

Key Concepts

TAM/SAM/SOM Framework

The three-tier market sizing model:

Total Addressable Market (TAM):

  • The total market demand for a product or service
  • "If we captured 100% of the market, what's the revenue?"
  • Broadest possible market (no constraints)

Serviceable Available Market (SAM):

  • The segment of TAM your company can realistically target
  • Narrowed by geography, firmographics, demographics, or product constraints
  • "Who can we actually reach with our product?"

Serviceable Obtainable Market (SOM):

  • The portion of SAM you can realistically capture
  • Accounts for competition, market constraints, go-to-market capacity
  • "What can we capture in the next 1-3 years?"

Why This Works

  • Top-down validation: TAM → SAM → SOM ensures estimates are grounded in reality
  • Investor-friendly: Standard framework VCs and execs understand
  • Citation-backed: Real data sources (Census, Statista, World Bank) add credibility
  • Adaptive: Questions adjust based on context (B2B vs. B2C, US vs. global, etc.)

Anti-Patterns (What This Is NOT)

  • Not a single-number guess: "The market is $10B" without supporting data
  • Not static: Markets evolve—reassess annually
  • Not a substitute for customer validation: Market size ≠ product-market fit

When to Use This

  • Pitching to investors or execs (need market size in deck)
  • Validating product ideas (is the market big enough?)
  • Prioritizing product lines (which has bigger opportunity?)
  • Setting growth targets (what's realistic to capture?)

When NOT to Use This

  • For internal tools with captive users (no external market)
  • Before defining the problem (market sizing requires clear problem space)
  • As the only validation (pair with customer research)

Facilitation Source of Truth

Use workshop-facilitation as the default interaction protocol for this skill.

It defines:

  • session heads-up + entry mode (Guided, Context dump, Best guess)
  • one-question turns with plain-language prompts
  • progress labels (for example, Context Qx/8 and Scoring Qx/5)
  • interruption handling and pause/resume behavior
  • numbered recommendations at decision points
  • quick-select numbered response options for regular questions (include Other (specify) when useful)

This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic.

Application

Use template.md for the full fill-in structure.

This interactive skill asks up to 4 adaptive questions, offering enumerated context-aware options at each step. The agent adapts questions based on previous responses.


Step 0: Gather Context (Before Questions)

Agent suggests:

Before we begin, it's helpful to have product context. If available, please share:

For Your Own Product:

  • Website copy (homepage, product pages, value prop statements)
  • Marketing emails or landing pages
  • Product descriptions or positioning statements
  • Case studies or customer testimonials
  • Sales deck or pitch materials

If You Don't Have a Product Yet:

  • Find a similar or adjacent product (competitor or analog)
  • Copy their website homepage, product description, or landing page
  • We'll use this as a reference point for market sizing

You can paste this content directly, or we can proceed with a brief description.

Why this helps:

  • Marketing materials already contain target audience, pain points, and value props
  • Analyzing real content (yours or competitors') grounds the analysis in reality
  • You can benchmark against similar products' market positioning

Optional Helper Script (Deterministic Math)

If you already have population and ARPU numbers (or a TAM estimate), you can run a deterministic helper to compute TAM/SAM/SOM and generate a Markdown table. This script does not fetch data or write files.

python3 scripts/market-sizing.py --population 5400000 --arpu 1000 --sam-share 30% --som-share 10%

Question 1: Problem Space

Agent asks: "Based on the context you've provided (or will describe), what problem space are you exploring for market sizing?"

Offer 4 enumerated examples (user can select by number or write custom):

  1. B2B SaaS productivity — E.g., "Workflow automation for small business operations" (like Zapier, Integromat)
  2. Consumer fintech — E.g., "Personal budgeting app for Gen Z users" (like Mint, YNAB)
  3. Healthcare/telehealth — E.g., "Mental health support for remote workers" (like BetterHelp, Talkspace)
  4. E-commerce enablement — E.g., "Payment processing for online sellers" (like Stripe, Square)

Or write your own problem space description based on the marketing materials you shared.

Tip: If you provided website copy or marketing materials, the agent can extract the problem space from phrases like:

  • "We help [target] solve [problem]"
  • "The #1 solution for [use case]"
  • Customer pain points in testimonials or case studies

User response: [Selection or custom description]


Question 2: Geographic Region

Agent asks: "What geographic region are you targeting?"

Offer 4 enumerated options (adapted based on problem space):

  1. United States — Best for detailed Census Bureau data, BLS stats, robust industry reports
  2. European Union — Use Eurostat, local statistical agencies; note GDPR/compliance considerations
  3. Global — World Bank, IMF data; broader but less granular
  4. Specific country/region — E.g., "Canada," "Southeast Asia," "Latin America"

Or specify your own region.

User response: [Selection or custom]

Adaptation logic:

  • If user selected B2B SaaS (Question 1, Option 1) → Emphasize US/EU markets (mature SaaS adoption)
  • If user selected Consumer fintech (Question 1, Option 2) → Mention emerging markets (higher mobile adoption)

Question 3: Industry/Market Segments

Agent asks: "What specific industry or market segments does this problem space relate to?"

Offer 4 enumerated options (adapted based on problem space + geography):

Example (if Question 1 = B2B SaaS, Question 2 = US):

  1. SMB services sector — 5.4M businesses, $1.2T revenue (US Census, 2023)
  2. Professional services (legal, accounting) — 1.1M firms, $850B revenue (IBISWorld, 2023)
  3. Healthcare providers — 900K practices, $4T industry (BLS, 2023)
  4. Tech/software companies — 500K firms, $1.8T revenue (Statista, 2023)

Or describe your own industry segment.

User response: [Selection or custom]

Adaptation logic:

  • If Question 1 = Consumer fintech, offer consumer segments (e.g., "Gen Z 18-25," "Millennials 25-40")
  • If Question 1 = Healthcare, offer segments (e.g., "Primary care physicians," "Therapists/counselors")

Question 4: Potential Customers (Demographics/Firmographics)

Agent asks: "Who are the potential customers affected by this problem?"

Offer 4 enumerated options (adapted based on previous answers):

Example (if Question 1 = B2B SaaS, Question 3 = SMB services sector):

  1. SMBs with 10-50 employees — 1.2M businesses, $400B revenue (Census Bureau, 2023)
  2. SMBs with 50-250 employees — 600K businesses, $800B revenue (Census Bureau, 2023)
  3. Solo entrepreneurs/freelancers — 3.5M self-employed, $200B revenue (BLS, 2023)
  4. Service businesses with online presence — 2M businesses, $600B e-commerce (Statista, 2023)

Or describe your own customer segment (firmographics, demographics, income, etc.).

User response: [Selection or custom]


Output: Generate TAM/SAM/SOM Analysis

After collecting responses, the agent generates a structured analysis:

# TAM/SAM/SOM Analysis

**Problem Space:** [User's input from Question 1]
**Geographic Region:** [User's input from Question 2]
**Industry/Market Segments:** [User's input from Question 3]
**Potential Customers:** [User's input from Question 4]

---

## Total Addressable Market (TAM)

**Definition:** The total market demand if you captured 100% of potential customers in the problem space.

**Population Estimate:** [Calculated from data sources]
- **Source:** [Citation, e.g., "US Census Bureau, 2023"]
- **Calculation:** [Show math, e.g., "5.4M SMBs × $1.2T revenue = $1.2T TAM"]

**Market Size Estimate:** $[X] billion/million
- **Source:** [Industry report citation]
- **URL:** [Clickable link to source]

---

## Serviceable Available Market (SAM)

**Definition:** The segment of TAM you can realistically target with your product (narrowed by geography, firmographics, product fit).

**Segment of TAM:** [User's narrowed segment from Question 4]

**Population Estimate:** [Calculated]
- **Source:** [Citation]
- **Calculation:** [Show math, e.g., "1.2M SMBs with 10-50 employees"]

**Market Size Estimate:** $[X] billion/million
- **Source:** [Citation]
- **URL:** [Link]

**Assumptions:**
- [List key assumptions, e.g., "Assumes 50% of SMBs have budget for automation tools"]

---

## Serviceable Obtainable Market (SOM)

**Definition:** The portion of SAM you can realistically capture in the next 1-3 years, accounting for competition and market constraints.

**Realistically Capturable Market:** [Agent's estimation based on market maturity, competition]

**Population Estimate:** [Calculated]
- **Source:** [Citation]
- **Calculation:** [Show math, e.g., "1.2M SMBs × 5% market share (Year 1) = 60K customers"]

**Market Size Estimate:** $[X] million
- **Assumptions:**
  - [Competition assumption, e.g., "5 major competitors, market leader has 15% share"]
  - [GTM assumption, e.g., "Sales capacity: 50 customers/month in Year 1"]
  - [Conversion assumption, e.g., "10% trial-to-paid conversion"]

**Year 1-3 Projections:**
- **Year 1:** [X]K customers, $[X]M revenue (5% of SAM)
- **Year 2:** [X]K customers, $[X]M revenue (10% of SAM)
- **Year 3:** [X]K customers, $[X]M revenue (15% of SAM)

---

## Data Sources & Citations

- [Source 1: e.g., "US Census Bureau (2023). County Business Patterns. URL: census.gov"]
- [Source 2: e.g., "IBISWorld (2023). Professional Services Industry Report. URL: ibisworld.com"]
- [Source 3: e.g., "Statista (2023). SMB Software Market Size. URL: statista.com"]
- [Add all sources used]

---

## Validation Questions

1. **Does TAM align with industry reports?** [Compare to 3rd-party market research]
2. **Is SAM realistically serviceable?** [Can your GTM motion reach this segment?]
3. **Is SOM achievable given competition?** [Is 5-15% market share realistic in 3 years?]

---

## Next Steps

1. **Validate with customer interviews:** Does the problem resonate with target segment?
2. **Benchmark against competitors:** What market share do incumbents have?
3. **Refine SOM based on GTM capacity:** Can sales/marketing support this growth?
4. **Update annually:** Markets shift—reassess TAM/SAM/SOM yearly

---

**Would you like to refine any assumptions or explore a different segment?**

Examples

See examples/sample.md for a full TAM/SAM/SOM analysis example.

Mini example excerpt:

**TAM:** 5.4M SMBs × $2,000 ARPA = $10.8B
**SAM:** 1.2M SMBs × $2,000 ARPA = $2.4B
**SOM:** 5% of SAM = $120M

Common Pitfalls

Pitfall 1: TAM Without Citations

Symptom: "The market is $50B" (no source)

Consequence: Can't defend the number to investors or execs.

Fix: Cite industry reports (Gartner, IBISWorld, Statista) with URLs.


Pitfall 2: SOM Equals SAM

Symptom: "SAM is $5B, SOM is $5B" (assuming 100% capture)

Consequence: Unrealistic projection—no market has zero competition.

Fix: SOM should be 1-20% of SAM in Year 1-3, accounting for competition.


Pitfall 3: No Population Estimates

Symptom: Only dollar amounts, no customer counts

Consequence: Can't build sales/marketing plans without knowing customer volume.

Fix: Always include population (e.g., "1.2M businesses" or "60K customers in Year 1").


Pitfall 4: Static Assumptions

Symptom: TAM/SAM/SOM calculated once, never updated

Consequence: Stale data as markets shift.

Fix: Reassess annually. Markets grow/shrink, competition changes, new data emerges.


Pitfall 5: Ignoring GTM Constraints

Symptom: "SOM is 50% of SAM in Year 1" (but no sales team)

Consequence: SOM isn't realistic given GTM capacity.

Fix: Ground SOM in GTM constraints (sales capacity, marketing budget, conversion rates).


References

Related Skills

  • skills/positioning-statement/SKILL.md — TAM/SAM/SOM informs "For [target]" segment size
  • skills/problem-statement/SKILL.md — Problem space defines the market
  • skills/recommendation-canvas/SKILL.md — Market sizing informs business outcome projections

Optional Helpers

  • skills/tam-sam-som-calculator/scripts/market-sizing.py — Deterministic TAM/SAM/SOM calculator (no network access)

External Frameworks

  • Steve Blank, *The Four Steps to the Epiphany* (2005) — Market sizing for startups
  • Lean Startup methodology — Validate market size with experiments, not just desk research

Data Sources (For Citations)

  • US: US Census Bureau, Bureau of Labor Statistics, IBISWorld, Statista
  • Europe: Eurostat, local statistical agencies
  • Global: World Bank, IMF, Gartner, Forrester

Dean's Work

  • TAM/SAM/SOM Prompt Generator (multi-turn adaptive market sizing)

Skill type: Interactive Suggested filename: tam-sam-som-calculator.md Suggested placement: /skills/interactive/ Dependencies: None (standalone interactive skill)

平台分布

Codex

35.72%
按下载量换算2,370

Claude

31.2%
按下载量换算2,070

Cursor

16.56%
按下载量换算1,099

Gemini CLI

9.13%
按下载量换算606

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可疑

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需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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