The Dossier Rubric — how investors score a seed-stage dataroom

Every module gets one integer. 1 to 10.

10/10

Sequoia-grade

Investor-ready. A partner forwards it internally. No edit required before send.

7–9/10

Strong

Substantive content with a clear gap — typically a missing source, a missing number, or one bullet that's generic.

4–6/10

Generic

Reads like every other deck — boilerplate, category-level claims, no proof.

1–3/10

Unsalvageable

Buzzword soup or absent entirely. Section needs a rewrite from inputs, not edits.

When the source material is silent on a module, the framework scores it 1 and emits a NEEDS INPUT instead of inventing one. Nothing is hallucinated to fill a gap — silence is a finding, not a defect.

Ten modules, ten rubrics.

Each module below shows the question the framework asks, the job it does for the investor, and the integer-by-integer scoring criteria. Deep-link a module by its anchor —/rubric#module-traction.

One-liner

Answers 'what does this company actually do?' in five seconds, before the partner closes the tab.

What the framework asks

Evaluate this company's one-liner. A one-liner is 6–12 words that name the product, the buyer, and the category in a way a stranger understands in under five seconds.

Scoring · 1 to 10

Score 10 = instantly clear, 6–12 words, names product + buyer + category, earns a second read. Score 7 = clear but generic or one word too long. Score 4 = buzzword-heavy or requires explanation. Score 1 = marketing fluff, no one understands what it is or who buys it.

#module-one-liner

Investment thesis

Answers 'why is this venture-scale?' — 3–5 specific, non-obvious reasons the round gets returned.

What the framework asks

Evaluate the investment thesis. It should be 3–5 bullets, each a sharp, non-obvious reason this is a venture-scale opportunity — moat, timing, distribution edge, unfair team, pricing power.

Scoring · 1 to 10

Score 10 = 3–5 bullets that a Sequoia partner would forward internally, each non-obvious and defended. Score 7 = 3 bullets that are reasonable but one is generic. Score 4 = category-level claims only ('AI is huge'). Score 1 = no thesis; marketing language only.

#module-investment-thesis

Company overview

Answers 'why noticed this problem first?' — the founder-insight origin story, not the mission statement.

What the framework asks

Evaluate the company overview. It should be ≤150 words covering mission, vision, and a founder-insight origin story that explains why this team noticed this problem first.

Scoring · 1 to 10

Score 10 = ≤150 words, clear mission, specific founder insight, no jargon. Score 7 = clear but generic origin. Score 4 = boilerplate 'we believe AI should be accessible' language. Score 1 = no differentiated story.

#module-company-overview

Product

Answers 'what gets shipped and why is it different?' — what it is, how it works, what the obvious alternative is.

What the framework asks

Evaluate the product description. It should be ≤200 words covering what the product is, its 2–3 key capabilities, and its differentiation from the obvious alternatives (incumbents or DIY).

Scoring · 1 to 10

Score 10 = ≤200 words, clear what + how + different, investor understands it in one read. Score 7 = clear what, weak differentiation. Score 4 = feature list without a clear product story. Score 1 = jargon soup, unclear what gets shipped.

#module-product

Market

Answers 'how big and why now is it accessible?' — defensible bottom-up sizing plus the trends that favor this company.

What the framework asks

Evaluate the market section. It should be ≤200 words covering TAM / SAM / SOM with defensible sourcing, plus 1–2 specific market trends that favor this company.

Scoring · 1 to 10

Score 10 = ≤200 words, defensible bottom-up numbers with sources, 1–2 specific trends, no fluff. Score 7 = numbers present but weak methodology. Score 4 = top-down 'Gartner says $100B' only. Score 1 = no numbers or meaningless TAM math.

#module-market

Business model

Answers 'who pays, how much, what are the unit economics?' — pricing, buyer, gross-margin direction.

What the framework asks

Evaluate the business model section. It should be ≤150 words covering how the company makes money, specific pricing (tiers, ACV), and unit economics signals (gross margin, CAC, LTV direction).

Scoring · 1 to 10

Score 10 = ≤150 words, specific pricing, named buyer, directional unit economics. Score 7 = pricing clear, unit economics absent. Score 4 = 'subscription model' without numbers. Score 1 = no pricing, no buyer, no economics.

#module-business-model

Traction

Answers 'what's working?' — revenue, growth rate, retention, named logos. Every number sourced.

What the framework asks

Evaluate the traction section. It should be facts-only: revenue, MRR/ARR, users, growth rate, named logos, retention cohorts. Every number must be attributable to a source. Vanity metrics (impressions, signups without activation) are weaknesses.

Scoring · 1 to 10

Score 10 = revenue + growth rate + named logos + retention, all sourced. Score 7 = revenue and logos but no retention. Score 4 = vanity metrics only. Score 1 = no traction data or unsourced claims. If traction is absent, tenOfTen must be 'NEEDS INPUT: <specific data>'.

#module-traction

Founder / team

Answers 'why this team?' — concrete founder-market fit, prior wins, key hires already in seats.

What the framework asks

Evaluate the founder/team section AND extract the founding team as structured cards. The prose `tenOfTen` should be ≤150 words: the why-us story tying founder experience to this specific problem, prior wins named, key hires. The `founders` array is one object per FOUNDER. For each founder, pull only what the source actually states — never invent. Leave role/bio empty and omit linkedinUrl/email when the source is silent.

Scoring · 1 to 10

Score 10 = ≤150 words, concrete founder-market fit, prior wins named, key hires listed. Score 7 = strong bios but why-us implicit. Score 4 = generic 'seasoned entrepreneurs'. Score 1 = no bios or no credibility signal.

#module-founder-team

Why now

Answers 'why does this exist now, not two years ago?' — a named catalyst (model release, regulation, behavior shift).

What the framework asks

Evaluate the why-now section. It should be ≤150 words identifying the specific tech shift, regulatory event, or behavior change that makes this opportunity viable now and not earlier.

Scoring · 1 to 10

Score 10 = ≤150 words, one sharp why-now with a named catalyst (model release, regulation, platform shift). Score 7 = plausible why-now but soft. Score 4 = 'AI is everywhere'. Score 1 = no why-now.

#module-why-now

Press / credibility

Answers 'what social proof is verifiable?' — tier-one press, operator-grade advisors, partnerships.

What the framework asks

Evaluate the press and credibility section. Facts only: tier-one press mentions, named advisors, accolades, partnerships, accelerator acceptance. Flag paid or contributor-network placements as weak signals.

Scoring · 1 to 10

Score 10 = tier-one press + named operator-advisors + partnerships, all verifiable. Score 7 = two of the three. Score 4 = logos-only with no context. Score 1 = no press, no advisors, no partnerships. If absent, tenOfTen must be 'NEEDS INPUT: <specific data>'.

#module-press-credibility

Every module gets one integer. 1 to 10.

10/10

Sequoia-grade

Investor-ready. A partner forwards it internally. No edit required before send.

7–9/10

Strong

Substantive content with a clear gap — typically a missing source, a missing number, or one bullet that's generic.

4–6/10

Generic

Reads like every other deck — boilerplate, category-level claims, no proof.

1–3/10

Unsalvageable

Buzzword soup or absent entirely. Section needs a rewrite from inputs, not edits.

Ten modules, ten rubrics.

Each module below shows the question the framework asks, the job it does for the investor, and the integer-by-integer scoring criteria. Deep-link a module by its anchor —/rubric#module-traction.

One-liner

Answers 'what does this company actually do?' in five seconds, before the partner closes the tab.

What the framework asks

Evaluate this company's one-liner. A one-liner is 6–12 words that name the product, the buyer, and the category in a way a stranger understands in under five seconds.

Scoring · 1 to 10

#module-one-liner

Investment thesis

Answers 'why is this venture-scale?' — 3–5 specific, non-obvious reasons the round gets returned.

What the framework asks

Evaluate the investment thesis. It should be 3–5 bullets, each a sharp, non-obvious reason this is a venture-scale opportunity — moat, timing, distribution edge, unfair team, pricing power.

Scoring · 1 to 10

#module-investment-thesis

Company overview

Answers 'why noticed this problem first?' — the founder-insight origin story, not the mission statement.

What the framework asks

Evaluate the company overview. It should be ≤150 words covering mission, vision, and a founder-insight origin story that explains why this team noticed this problem first.

Scoring · 1 to 10

#module-company-overview

Product

Answers 'what gets shipped and why is it different?' — what it is, how it works, what the obvious alternative is.

What the framework asks

Evaluate the product description. It should be ≤200 words covering what the product is, its 2–3 key capabilities, and its differentiation from the obvious alternatives (incumbents or DIY).

Scoring · 1 to 10

#module-product

Market

Answers 'how big and why now is it accessible?' — defensible bottom-up sizing plus the trends that favor this company.

What the framework asks

Evaluate the market section. It should be ≤200 words covering TAM / SAM / SOM with defensible sourcing, plus 1–2 specific market trends that favor this company.

Scoring · 1 to 10

#module-market

Business model

Answers 'who pays, how much, what are the unit economics?' — pricing, buyer, gross-margin direction.

What the framework asks

Evaluate the business model section. It should be ≤150 words covering how the company makes money, specific pricing (tiers, ACV), and unit economics signals (gross margin, CAC, LTV direction).

Scoring · 1 to 10

#module-business-model

Traction

Answers 'what's working?' — revenue, growth rate, retention, named logos. Every number sourced.

What the framework asks

Scoring · 1 to 10

#module-traction

Founder / team

Answers 'why this team?' — concrete founder-market fit, prior wins, key hires already in seats.

What the framework asks

Scoring · 1 to 10

#module-founder-team

Why now

Answers 'why does this exist now, not two years ago?' — a named catalyst (model release, regulation, behavior shift).

What the framework asks

Evaluate the why-now section. It should be ≤150 words identifying the specific tech shift, regulatory event, or behavior change that makes this opportunity viable now and not earlier.

Scoring · 1 to 10

Score 10 = ≤150 words, one sharp why-now with a named catalyst (model release, regulation, platform shift). Score 7 = plausible why-now but soft. Score 4 = 'AI is everywhere'. Score 1 = no why-now.

#module-why-now

Press / credibility

Answers 'what social proof is verifiable?' — tier-one press, operator-grade advisors, partnerships.

What the framework asks

Scoring · 1 to 10

#module-press-credibility

How investors score a seed-stage dataroom.

Every module gets one integer. 1 to 10.

Ten modules, ten rubrics.

One-liner

Investment thesis

Company overview

Product

Market

Business model

Traction

Founder / team

Why now

Press / credibility

Score your dataroom against the rubric — free.

How investors score a seed-stage dataroom.

Every module gets one integer. 1 to 10.

Ten modules, ten rubrics.

One-liner

Investment thesis

Company overview

Product

Market

Business model

Traction

Founder / team

Why now

Press / credibility

Score your dataroom against the rubric — free.