Analyze Startup Markets and Finances
Build startup market, financial, competitive, and hiring analyses with cited data, explicit assumptions, and stage-aware recommendations.
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Why it matters
Leverage expert startup analysis to size markets, build financial models, and develop competitive strategies for early-stage companies seeking funding and growth.
Outcomes
What it gets done
Perform TAM/SAM/SOM analysis and market research.
Develop 3-5 year financial models with scenario planning.
Conduct competitive landscape assessments using strategic frameworks.
Provide actionable insights for fundraising and strategic decision-making.
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-startup-analyst | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
Reports
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Overview
Startup Analyst covers market sizing, financial planning, competitive strategy, team design, and metrics for pre-seed through Series A companies. It requires cited data, transparent assumptions, and validated calculations. Use it for fundraising preparation, board reporting, strategic planning, and startup operating decisions. Adapt the analysis to stage, business model, founder context, and evidence quality.
What it does
Startup Analyst is a skill for early-stage business analysis from pre-seed through Series A. It combines market sizing, financial modeling, competitive strategy, team planning, startup metrics, and fundraising preparation. Its approach begins with the company's stage, business model, and specific question, then gathers data, applies relevant frameworks, shows calculations, validates findings, and presents recommendations with cited sources and publication dates.
Market analysis uses bottom-up, top-down, and value-theory methods for TAM, SAM, and SOM. It evaluates credible sources, triangulates estimates, and applies business-model-specific approaches for SaaS, marketplaces, consumer products, B2B, and fintech. Public-company analysis and industry research help validate opportunity estimates and growth assumptions.
Financial planning covers cohort revenue, CAC, LTV, payback, cash flow, runway, burn, efficiency, fundraising scenarios, break-even, and profitability. Models span three to five years with conservative, base, and optimistic scenarios. Competitive work applies Porter's Five Forces, Blue Ocean Strategy, positioning maps, landscape research, differentiation, and sustainable-advantage assessment. Strategic advisory extends to go-to-market, pricing and packaging, customer prioritization, partnerships, and market entry.
Team planning covers role sequencing by stage, compensation benchmarking, equity allocation, reporting structures, organizational design, and full-time versus contractor choices. Metrics work considers growth, retention, unit economics, burn multiple, magic number, Rule of 40, and investor-focused indicators.
When to use - and when NOT to
Use it for startup market questions, financial projections, unit economics, competitive landscapes, hiring plans, KPI selection, business strategy, board preparation, or investor materials. Stage awareness changes the emphasis: pre-seed focuses on product-market fit signals, seed balances growth and efficiency, and Series A examines scalable, repeatable economics.
The workflow rejects unsupported claims, overly optimistic assumptions, skipped validation, missing competitive context, generic advice detached from the company, and uncited data. Clarify goals, constraints, required inputs, permissions, boundaries, and success criteria. Keep expert review and environment-specific validation where relevant.
Industry-specific emphasis includes MRR, NDR, and CAC payback for SaaS; GMV, take rate, and liquidity for marketplaces; retention, virality, and engagement for consumer products; and ACV, sales efficiency, and win rate for B2B. Compensation guidance includes US-focused 2024 benchmarks, which makes source dates part of interpretation.
Inputs and outputs
Inputs include the business model, stage, market question, financial assumptions, operating constraints, available data, and decision context. Outputs include investor-ready reports, business cases, pitch support, board templates, financial models, and actionable recommendations. Analysis uses structured sections, tables, formulas, sources, assumptions, benchmarks, and next steps.
Calculations show the formula, input values, steps, result with units, interpretation, and benchmark comparison. Recommendations identify rationale, expected outcomes, resources, sequencing, risks, and mitigation. Data quality and limitations remain visible, and findings are cross-checked with alternative methods where possible.
Integrations
Plugin commands include /market-opportunity for market sizing, /financial-projections for models, and /business-case for business-case documents. Related skills provide market sizing, startup financial modeling, competitive landscapes, team composition, and metrics frameworks. Web search supplies current market data, while read/write tools and calculation capabilities support document creation and analysis.
Who it's for
The skill serves founders, entrepreneurs, and early-stage investors. It adapts explanations for first-time founders, more tactical analysis for repeat founders, business and GTM guidance for technical founders, and product or technical strategy guidance for business founders. Investor context distinguishes angels, seed and Series A venture investors, and corporate venture investors.
Source README
Expert business analyst focused exclusively on startup-stage companies, providing practical, actionable analysis for entrepreneurs, founders, and early-stage investors. Combines rigorous analytical frameworks with startup-specific best practices to deliver insights that drive fundraising success and strategic decision-making.
FAQ
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