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Agent Skill · 研究检索

tam-sam-som(三三颂)

tam-sam-som 用于查找、检索和筛选相关信息,适合在 OpenClaw 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 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 24,581。

总安装 3,975周安装 164GitHub Stars 公开资料未说明下载 1,299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
MIT-0
版本
1.0.0

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(三三颂)
来源仓库:https://github.com/owenrao/tam-sam-som
安装命令:
openclaw skills install tam-sam-som
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install tam-sam-som

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-som 用于制定严格来源的市场规模分析框架。适用于产品或业务相关的 TAM/SAM/SOM 测算需求。当用户询问市场规模或可寻址市场时应优先使用此技能。输出基于公开数据估算,实际数值可能存在偏差。建议结合行业报告交叉验证关键假设参数。

tam-sam-som 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

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 OpenClaw;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 openclaw skills install tam-sam-som;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

tam-sam-som 怎么安装?

在终端执行 openclaw skills install tam-sam-som。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 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

tam-sam-som 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

tam-sam-som 用的人多吗?

公开数据是累计安装 3,975 次,近一周安装 164 次,下载 1,299 次。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 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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

三三颂 · 本页

3,975—只读MIT-0通过

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

name
market-sizing
description
Produce a rigorous, sourced TAM/SAM/SOM market sizing for any product or business. Use this skill whenever a user asks about market size, total addressable market, SAM, SOM, or market opportunity — across any industry including SaaS, AI tools, consumer brands, F&B, fashion, beauty, packaging, automotive, and more.
version
v2

TAM / SAM / SOM Market Sizing

Produce both a bottom-up and a top-down analysis for every engagement. Both methods are required — they serve different purposes and must be reconciled. The goal is a defensible, sourced output — not a fast estimate.


When to use this skill

Trigger on any prompt that contains:

  • "TAM", "SAM", "SOM", or "market size"
  • "How big is the market for X"
  • "Total addressable market", "serviceable market", "obtainable market"
  • "Market sizing for [product/company]"
  • Investor deck context requiring market opportunity quantification

Loading examples

Before calculating, check the examples/ directory for a file matching the product's category. Load the closest match to calibrate data sources, filter logic, and ACV anchors before you begin.

FileUse when product is...
examples/b2b-saas.mdSoftware / AI tool sold to businesses
examples/b2c-consumer-brand.mdConsumer packaged goods, DTC brands, subscriptions
examples/b2b-physical.mdPhysical goods or materials sold to businesses

If no exact match exists, load the closest file and adapt.


Pre-flight: Classify the product before doing anything else

Before searching or calculating, classify the product along these two axes. The classification directly determines which data sources to use and which pricing method applies.

Axis 1 — Business model

CodeTypeRevenue unitPricing anchor
B2B-SaaSSoftware sold to businessesAnnual contract (ACV)10–20% of economic value created
B2B-PhysicalPhysical goods sold to businessesPer-unit price × annual volumeGross margin benchmarks by industry
B2C-BrandConsumer product (any category)Revenue per customer per yearAvg. purchase price × purchase frequency
B2C-SubscriptionConsumer subscriptionMonthly/annual subscription feeStated price or comp pricing
Marketplace/PlatformTakes % of GMVTake rate × GMVIndustry take rate benchmarks

Axis 2 — Market geography

  • US-only: Use US Census, NAICS codes, US industry associations
  • Global: Use global market reports, then apply regional share (US ~25–30% of global GDP; NA ~32%; APAC ~38%)
  • Single city/region: Use metro area population data + category penetration rates

Step-by-step workflow (universal)

Step 0 - Data Gathering

Since accuracy and reliability are key of this task, make sure you collect enough reliable data from reliable sources before the calculation. Limited estimation is fine with enough evidence support, but any kind of data making up or hallucination without evidence during the calculation and output phase is a fraud.

STEP 1 — Define the revenue unit

Before any market data search, lock down exactly what the product sells, to whom, and at what price.

Required inputs:

  • Who is the buyer? (job title / consumer demographic)
  • What is the unit of sale? (per seat, per SKU, per kg, per subscription, per transaction)
  • What is the price? (stated, or estimated by comp analysis)
  • What is the purchase frequency? (one-time, monthly, annual, recurring)

If price is unknown: Search "[product category] average price" OR "[closest competitor] pricing" and anchor to the median. For B2B-SaaS, also apply the 10–20% value rule: price = 10–20% of annual economic value the product creates for the customer.

Output of Step 1: A single sentence — *"The revenue unit is [X] sold to [Y] at [Z]/year."*

STEP 2 — TAM (Total Addressable Market)

TAM = the maximum theoretical revenue if every potential buyer purchased the product.

2A — Bottom-up method (PREFERRED for all product types)

For B2B products:

  1. Search for the number of firms in the target industry

- US: Use NAICS code lookup — search "NAICS [code] number of firms US" or site:siccode.com NAICS [code] - Global: Use IBISWorld, Statista, or national business registries

  1. Estimate the % that are genuinely relevant (apply product-fit filter at this stage only if very obvious — e.g. residential-only firms for a commercial B2B product)
  2. TAM = Total relevant firms × ACV

For B2C products:

  1. Find the total consumer population in the target geography (US Census, APPA, Statista, trade associations)
  2. Find the % in the target demographic/behavioral segment
  3. TAM = Segment population × annual spend per person

Search queries to use:

  • "[industry] number of [businesses/firms/brands] US 2024"
  • "NAICS [code] firm count employees revenue"
  • "[consumer category] number of [households/users/owners] US"
  • "[category] market size 2024" (for cross-reference only — not the primary method)
2B — Top-down method (SECONDARY cross-check)
  1. Find total category market size from analyst reports (Grand View, IMARC, Mordor, Precedence, IBISWorld)
  2. Apply funnel: Total market → relevant segment → product-type share → geography
  3. Search: "[category] software/product market size 2024" or "[category] industry revenue US 2024"

Rule: Bottom-up is the primary method. Top-down is the cross-check. Both results should be reported. If they diverge significantly (>2×), explain why (e.g. top-down only counts current spenders; bottom-up counts total potential).

TAM output format:
  • Single dollar figure (round to nearest $100M for large markets, $10M for mid-size)
  • Conservative range (low–high)
  • The math shown explicitly: N firms × $X ACV = $Y or N consumers × $Z annual spend = $Y

STEP 3 — SAM (Serviceable Addressable Market)

SAM = the subset of TAM that the specific product can actually serve today, given its business model, geography, language, and product fit.

Universal filter checklist — apply all that are relevant:

FilterTypical reductionHow to estimate
GeographyVariesIf US-only product, filter out non-US. If city-level, apply metro population fraction.
Product-fit segment30–60% reductionRemove segments the product doesn't serve (e.g. residential-only for commercial SaaS; solo operators who can't justify the cost)
Tech/channel readiness10–30% reduction% of target customers with internet access, cloud tools, or relevant distribution channel access
Language/regulatoryVariesOnly relevant for global products
Willingness to pay tier20–40% reductionRemove segments priced out of the product's tier

Formula: SAM = TAM × Filter₁ × Filter₂ × ... × Filterₙ

Blended ACV for SAM: If there are multiple customer segments (SME vs. mid-market, or mass vs. premium), calculate a weighted average ACV: Blended ACV = (Segment_A_ACV × weight_A) + (Segment_B_ACV × weight_B)

Search queries for filter data:

  • "[industry] percentage [commercial/residential/enterprise/SMB]"
  • "[industry] small business cloud software adoption rate"
  • "[consumer category] premium vs mass market share"
SAM output format:
  • Single dollar figure with conservative range
  • Every filter listed with its % reduction and data source
  • Blended ACV (if applicable)

STEP 4 — SOM (Serviceable Obtainable Market)

SOM = the portion of SAM the product can realistically capture in a defined timeframe (typically 3 years / Year 1–3 ramp).

Penetration rate benchmarks by product type:

Product typeYear 1Year 3Source basis
New B2B SaaS (no category)0.1–0.3% of SAM1.5–3% of SAMAndreessen Horowitz, OpenView benchmarks
New B2B SaaS (established category)0.3–0.8%3–7%Category incumbents' early growth data
New B2C consumer brand (retail)0.05–0.2% of SAM0.5–2%Nielsen new brand launch data
New B2C DTC subscription0.1–0.5%1–4%DTC cohort benchmarks
New B2B physical product0.2–0.5%2–5%Trade distribution ramp benchmarks

Cross-validation method: Find 2–3 comparable companies (same category, similar stage) and anchor SOM to their reported early ARR/revenue. Search: "[similar company] [Series A / early revenue / ARR] raised [year]"

Formula:

  • SOM (Year 1) = SAM × Year 1 penetration rate
  • SOM (Year 3) = SAM × Year 3 penetration rate
  • Customer count = SOM ÷ Blended ACV (sanity check — does this number of customers feel achievable given go-to-market?)
SOM output format:
  • Year 1 and Year 3 ARR/revenue targets
  • Customer count at each stage
  • Named comparable company validations
  • Penetration rate used (with justification)

STEP 5 — Reconcile and flag conflicts

After running both methods:

  1. If bottom-up TAM > top-down TAM: Usually because the product creates new demand (not just shifting existing spend). State this explicitly.
  2. If bottom-up TAM < top-down TAM: Often because the product is a niche within a large category. State which definition is being used.
  3. Always present a range, not a single number, for TAM and SAM. Single numbers imply false precision.
  4. Flag the 3 most sensitive assumptions — the ones where a change of ±20% would materially shift the output. These are the assumptions to validate with primary research.

Source hierarchy (use in this order, stop when satisfied)

Tier 1 — Primary/official sources (highest credibility)

  • US Census Bureau / Economic Census — firm counts, employment, revenue by NAICS code
  • NAICS/SIC code databases (siccode.com, census.gov) — industry firm counts
  • Industry trade associations (APPA for pets, CFMA for construction, NMMA for marine, etc.)
  • SEC filings / public company 10-Ks — addressable market disclosures
  • Government labour/business statistics (BLS, SBA, ONS)

Tier 2 — Reputable market research

  • IBISWorld, Grand View Research, Mordor Intelligence, IMARC Group, Precedence Research, Statista
  • Use these for: category market size, CAGR, segment shares
  • Cross-reference at least 2 sources — market research firms often disagree by 20–40%

Tier 3 — Comparable company evidence

  • Funding announcements (TechCrunch, Crunchbase, Construction Dive, etc.)
  • Public company revenue disclosures at IPO/Series B
  • Use for: SOM cross-validation, ACV benchmarks, growth rate validation

Tier 4 — Pricing/ACV benchmarks

  • Competitor pricing pages (direct)
  • G2, Capterra, Trustpilot reviews mentioning price
  • Stripe, Monetizely, OpenView pricing guides (for B2B SaaS)

ACV / pricing benchmarks by product type

Product typeTypical ACV/ASPNotes
SMB B2B SaaS (1–50 employees)$3,000–$15,000/yr10–20% of value created
Mid-market B2B SaaS (50–500 employees)$15,000–$60,000/yr
Enterprise B2B SaaS (500+ employees)$60,000–$500,000+/yr
Consumer subscription (premium)$100–$600/yr
Consumer packaged goods (premium)$30–$150/order, 6–12×/yr
B2B physical product (SMB)$5,000–$50,000/yrDepends heavily on industry
B2C DTC brand (avg. LTV proxy)2–3× first-order value

Common errors — check before finalising

ErrorHow to catch it
"1% of a $10B market" without proofAlways verify with bottom-up customer count
Top-down only, no bottom-upAlways run both methods
Using global TAM when product is US-onlyApply geography filter explicitly
Including non-buyers in TAM (e.g. residential firms in a commercial B2B)Apply product-fit filter before TAM finalisation
SOM penetration rate not benchmarkedAlways cite at least one comp company
ACV not grounded in value or comp pricingAlways show the value math or comp reference
Treating TAM as "market size from report" uncriticallyCheck the report's definition matches your product's scope
Single number without rangeAlways show low–high range

Industry-specific data source cheat sheet

IndustryBest firm-count sourceBest market-size sourceKey trade association
Construction / TradesNAICS via siccode.com or CensusIBISWorld, CFMA BenchmarkerCFMA, AGC, NECA
Pet / Consumer packaged goodsCensus NAICS 311APPA, Grand View, IMARCAPPA, PFI
Food & BeverageCensus NAICS 311/312Mordor, Grand View, MintelFMI, GMA
Beauty / Personal careCensus NAICS 325620Euromonitor, Grand ViewPBA, CEW
Fashion / ApparelCensus NAICS 315McKinsey Fashion Report, StatistaAAFA
SaaS / SoftwareCrunchbase, G2 categoriesGartner, IDC, ForresterVaries
AutomotiveNAICS 441/336Ward's Auto, IHS MarkitNADA, SEMA
B2B PackagingCensus NAICS 322/326Grand View, MordorPMMI, FPA

Output format

The output file is where you calculations are made. After collecting necessary data, make a step-by-step analysis & calculation on the file, finally yielding a summary and a comparison. Produce a structured markdown document containing:

  • Both methods in full, each covering TAM → SAM → SOM completely before moving to the next method. Each method include 3 sections (TAM, SAM, SOM), each with: headline figure + range, full calculation shown line by line, and key assumptions&sources listed
  • A standalone section for all used figures' sources & assumptions.
  • A summary: table with TAM / SAM / SOM figures (bottom-up and top-down side by side); a method comparison note explaining divergence if bottom-up and top-down differ by >2×

The following is an example markdown output with a structure you should follow:

"""

Market Sizing: BuildFlow AI

*AI-powered invoicing automation for HVAC and Electrical subcontractors — United States*


Method 1: Bottom-up

TAM

InputValueSource
HVAC firms (NAICS 238220)88,738siccode.com / US Census
Electrical firms (NAICS 238210)55,951siccode.com / US Census
% doing GC-facing commercial work55%SBA subcontractor mix data
ACV — HVAC SME tier$7,500/yr$1.5M avg. revenue × 0.5%; CFMA 2024
ACV — Electrical SME tier$10,000/yr$2.0M avg. revenue × 0.5%; CFMA 2024
ACV — mid-market tier (>$5M rev)$24,000/yrValue-based; comp: Siteline pricing
HVAC SME (48,806 × 82%):           40,021 × $7,500  = $300M
HVAC mid-market (48,806 × 18%):     8,785 × $24,000  = $211M
Electrical SME (30,773 × 82%):     25,234 × $10,000  = $252M
Electrical mid-market (30,773×18%): 5,539 × $24,000  = $133M
Value-based ceiling (5% leakage × 10–20% SaaS capture): ~$1.87B

→ TAM: $1.87B (range: $1.5B–$2.2B)

SAM

FilterReductionRemainingSource
Remove residential-only operators−40%47,748 firmsSBA / IBISWorld industry mix
Remove solo / owner-only operators−35%31,037 firmsCensus nonemployer statistics
Remove cloud / tech-unready firms−25%23,278 firmsConstruction tech adoption surveys 2024
Blended ACV:
  SME tier (70%):     $7,500  × 0.70 = $5,250
  Mid-market (30%):   $18,000 × 0.30 = $5,400
  Blended:                            = $10,650/yr

23,278 firms × $10,650 + mid-market uplift ≈ $560M

→ SAM: $560M (range: $430M–$690M)

SOM

Year% of SAMARRCustomers
Year 10.27%~$1.5M~140
Year 20.85%~$4.8M~450
Year 31.5–3.0%$8.4M–$16.8M790–1,580

*Benchmark: 1.5–3% of SAM by Year 3 — a.H./OpenView SaaS benchmarks for new B2B entrant in established category*

CompSignal
PayraRaised $15M (Edison Partners); AP automation for construction subcontractors
SitelineRaised $18M Series A; subcontractor billing / SOV management, comparable ICP
Adaptive Construction SolutionsBootstrapped to ~$5M ARR in 3 years; construction AR automation

→ SOM: $1.5M ARR (Year 1) / $8.4M–$16.8M ARR (Year 3), ~790–1,580 customers


Method 2: Top-down

TAM

Global construction accounting software (2025):  $2.64B  [Precedence Research]
× US share (76%):                                 $2.0B
× AP/AR segment (54.4%):                          $1.09B

→ TAM: $1.09B

SAM

Top-down TAM:                        $1.09B
× Specialty trade sub-share (~28%):  $305M
× HVAC + Electrical only (~50%):     $152M

→ SAM: $152M

SOM

SAM (top-down):              $152M
× 3% Year 3 penetration:     $4.6M

→ SOM: $0.4M ARR (Year 1) / $4.6M ARR (Year 3)


Sources

InputValue assumedSource
HVAC firms (NAICS 238220)88,738siccode.com / US Census
Electrical firms (NAICS 238210)55,951siccode.com / US Census
% GC-facing commercial work55%SBA subcontractor mix data
Avg. HVAC subcontractor revenue$1.5M/yrCFMA 2024 Benchmarker
Avg. Electrical subcontractor revenue$2.0M/yrCFMA 2024 Benchmarker
Subcontractor net profit margin2.2–3.5%CFMA 2024 Benchmarker
Profit lost to unbilled/errors~5% of revenueIndustry estimate
Global construction accounting software market$2.64B (2025)Precedence Research
AP/AR segment share54.4%Precedence Research
Cloud/tech readiness of small construction firms~75%Construction tech adoption surveys 2024
SaaS penetration benchmark (Year 3)1.5–3% of SAMa.H./OpenView SaaS benchmarks
Comp: Payra raise$15MEdison Partners announcement
Comp: Siteline raise$18M Series APublic announcement

Summary

Bottom-upTop-down
TAM$1.87B$1.09B
SAM$560M$152M
SOM — Year 1 / Year 3$1.5M / $8.4M–$16.8M ARR$0.4M / $4.6M ARR
Bottom-up preferred — top-down counts only existing software spend and misses the large paper/spreadsheet segment. Use top-down as the floor / downside scenario.

"""

Quality checklist before delivering output

  • [ ] Both bottom-up AND top-down methods calculated
  • [ ] Every input number has a named source
  • [ ] TAM and SAM shown as ranges, not single numbers
  • [ ] Blended ACV used where multiple customer segments exist
  • [ ] SOM penetration rate benchmarked against 1–2 comp companies
  • [ ] At least 3 sensitivity risks flagged
  • [ ] Part 1 markdown follows the Output Example structure exactly
  • [ ] Prose narration follows all 6 workflow steps
  • [ ] Top-down vs bottom-up divergence explained if >2×

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只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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