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by shingo imotasimota/agent-skills85 stars
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Simulating business strategy via short/mid/long-term scenario planning from financial, market, and competitive data. Applies SWOT/PESTLE/Porter, KPI forecasting, roadmaps. Does not write code.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/helm

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referencemarket-sizing-strategy.md

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Market Sizing for Strategic Context — Helm

Purpose: Use this file when Helm needs to incorporate market size data into strategic simulation, market entry evaluation, portfolio allocation, or growth planning.

Contents

  • Market sizing in strategic context
  • Consumption from Compete
  • Strategic application of TAM/SAM/SOM
  • Market entry decision framework
  • Portfolio sizing
  • Templates

Market Sizing in Strategic Context

Helm's Role vs Compete's Role

Responsibility Owner Description
Market size estimation Compete Primary research, calculation, cross-verification
Strategic interpretation Helm Using market size for decisions, simulations, forecasts

Helm does not estimate market size from scratch. Helm consumes market sizing data from Compete (via COMPETE_TO_HELM handoff) or from provided context, and applies it to strategic frameworks.

When Helm Needs Market Sizing

Strategic question How market sizing helps
Should we enter this market? SAM validates sufficient opportunity
How fast can we grow? SOM vs SAM ratio reveals headroom
Should we invest or launch? TAM growth rate drives BCG quadrant
Which segment to prioritize? Segment-level SAM comparison
Is acquisition justified? Target's SAM + our SAM = combined opportunity
When do we hit diminishing returns? SOM approaching SAM ceiling signals pivot need

Strategic Application of TAM/SAM/SOM

Market Headroom Analysis

## Market Headroom: [Product/Segment]

### Current Position
- Current revenue: $[X]
- Current market share (of SAM): [X]%
- SOM: $[X] ([X]% of SAM)
- SAM: $[X] ([X]% of TAM)
- TAM: $[X]

### Headroom Assessment
| Metric | Value | Implication |
|---|---|---|
| SOM / SAM ratio | [X]% | [< 10% = early, 10-30% = growing, > 30% = nearing ceiling] |
| SAM / TAM ratio | [X]% | [< 20% = niche, 20-50% = focused, > 50% = broad] |
| TAM CAGR | [X]% | [< 5% = mature, 5-15% = growing, > 15% = high-growth] |
| Years to SAM ceiling | [X] years | [at current growth rate] |

### Strategic Implication
- Growth headroom: [abundant / adequate / limited / exhausted]
- Recommended strategy: [penetrate / expand SAM / expand TAM / diversify]

Market Size in Scenario Simulation

Integrate market sizing into Helm's 3-scenario model:

Baseline scenario:
  Revenue = SOM × execution factor (0.8-1.0)

Optimistic scenario:
  Revenue = SOM × (1 + market expansion factor)
  where market expansion = SAM growth + share gain

Pessimistic scenario:
  Revenue = SOM × (1 - competitive erosion factor)
  where competitive erosion = new entrant impact + churn increase

Market Entry Decision Framework

Go/No-Go Inputs from Market Sizing

## Market Entry Analysis: [Target Market]

### Market Attractiveness
| Factor | Score (1-5) | Weight | Weighted score |
|---|---|---|---|
| TAM size | | 15% | |
| TAM growth rate | | 20% | |
| SAM accessibility | | 20% | |
| Competitive intensity (inverse) | | 15% | |
| Margin potential | | 15% | |
| Strategic fit | | 15% | |
| **Total** | | 100% | **[X/5]** |

### Entry Threshold Rules
| Score | Decision |
|---|---|
| ≥ 4.0 | Strong go — prioritize entry |
| 3.0-3.9 | Conditional go — validate key assumptions |
| 2.0-2.9 | Weak — needs compelling strategic rationale beyond market size |
| < 2.0 | No go — insufficient opportunity |

### Simulation Integration
- Feed attractiveness score into Helm scenario simulation
- Model entry investment against SOM ramp-up timeline
- Include competitive response scenarios (from Compete wargaming if available)

Portfolio Sizing

Multi-Market Portfolio View

## Portfolio Market Sizing

| Product / Segment | TAM | SAM | SOM | Current revenue | Headroom | Priority |
|---|---|---|---|---|---|---|
| [Product A] | $X | $X | $X | $X | [X]% | H/M/L |
| [Product B] | $X | $X | $X | $X | [X]% | H/M/L |
| [Product C] | $X | $X | $X | $X | [X]% | H/M/L |

### BCG Integration
- Stars: [products with high TAM growth + high share]
- Cash Cows: [products with low TAM growth + high share]
- Question Marks: [products with high TAM growth + low share]
- Dogs: [products with low TAM growth + low share]

### Resource Allocation Recommendation
| Product | BCG quadrant | Recommended investment | Market sizing rationale |
|---|---|---|---|
| [Product A] | [quadrant] | [invest/maintain/launch/divest] | [TAM/SAM/SOM justification] |

Templates

Compete-to-Helm Market Sizing Handoff

Expected format when receiving market sizing from Compete:

COMPETE_TO_HELM:
  market: "[market name]"
  tam: "$[X]"
  tam_cagr: "[X]%"
  sam: "$[X]"
  som: "$[X]"
  estimation_method: "[top-down / bottom-up / both]"
  cross_verification: "[aligned / divergent — details]"
  confidence: "[high / medium / low]"
  key_assumptions:
    - "[assumption 1]"
    - "[assumption 2]"
  competitive_context:
    market_structure: "[monopoly / oligopoly / fragmented]"
    top_3_share: "[X]%"
    our_position: "[leader / challenger / niche / entrant]"

If this handoff data is not available, Helm should request it via HELM_REQUEST_COMPETE or note the gap explicitly in assumptions.

2026 Market-Sizing Norms

The 2026 default for AI and SaaS pitch reviews is bottoms-up validation triangulated with top-down sanity-check — top-down alone is now the #1 red flag in VC pitch reviews (Waveup 2026).

  • Bottom-up baseline: Market Size = ACV × Number of Reachable Customers, where "reachable" is defined by ICP, geography, and channel — not by industry total revenue.
  • Common misuse to flag (Antler, Visible.vc, Qubit Capital 2026):
    • Quoting a customer's total revenue as your TAM (you can capture only the share they spend on solving the job).
    • Confusing "industry size" with "addressable software spend on this job."
    • Skipping SOM entirely — investors read missing SOM as inability to model customer acquisition.
  • Triangulation effect: Carta 2025 found founders who present both top-down and bottom-up close rounds ~40% faster because VCs can stress-test one against the other (Waveup 2026 TAM/SAM/SOM).

AI-Startup Sizing Pitfalls (2026)

Pitfall Why it fails Fix
"AI for X" TAM = entire X industry IT spend Ignores that AI is one feature, not the budget owner Anchor on the replaced budget (specific headcount or workflow), not the industry
Counting model API spend as your TAM That is OpenAI / Anthropic's TAM, not yours Your TAM is the value you generate above raw API access
Per-seat ARR projected on industry-wide headcount Assumes 100% replacement of seat-based work Model gradual workflow capture; introduce an attainable-share cap based on adoption-lifecycle stage
Carta-bench-driven sizing Anchor on valuation not market reality; AI seed valuations ran +42% over non-AI Q1 2026, distorting TAM expectations Disclose valuation reference separately from market sizing; do not let one inform the other

Strategic Implication for Helm Scenarios

  • For AI-first opportunities, build at least one pessimistic scenario where the underlying model provider absorbs the wrapper feature (see strategic-anti-patterns.md SP-12) — this caps SOM at the period before absorption.
  • For incumbent industries deploying AI as sustaining (per Christensen Institute 2025-2026 framing in disruption-detection.md), SOM grows but SAM share does not — model the expansion as ARPU lift, not new logos.

Source: SKILL.md on GitHub

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    The 'helm' skill is a comprehensive strategic analysis agent designed for business simulation and KPI forecasting. It utilizes frameworks like SWOT, PESTLE, and Porter's Five Forces to provide decision support. Security analysis confirms the skill is safe, with no detected malicious code, data exfiltration patterns, or obfuscation techniques. A minor surface for indirect prompt injection is noted due to the ingestion of external market data, which is standard for research-oriented agents.

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