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How scoring works

Methodology v2

Stage-aware, confidence-weighted scoring. Replaces the legacy GO/REFINE/KILL three-bucket verdict with a four-bucket decision and a per-lens confidence vector.

Each lens (audit-team, audit-market, audit-competition, …) emits two outputs that feed the v2 verdict:

  • Pass/fail — boolean, the lens's own rubric.
  • Confidence (0..1) — how strongly the lens trusts its conclusion given the evidence it gathered. Low confidence on a fail is a softer signal than high confidence on a fail.

compute_dealbreakers_v2 aggregates these into a four-bucket decision:

GO

All critical lenses pass with high confidence.

CONDITIONAL_GO

Pass with caveats — fixable gaps in 1-2 lenses.

REFINE

Material weaknesses; iterate before raising.

KILL

High-confidence dealbreaker(s) — pivot or drop.

Stage matters. The same lens output is weighted differently for an idea-stage founder vs a Series A applicant — a missing CFO is fatal at Series A and ignorable at idea stage. Stage is captured via setAuditStageSector on save.

Cross-lens consensus. When two lenses make contradictory claims (audit-market: “CAGR 30%” vs audit-competition: “saturated, no growth left”), we surface a consensus warning and downgrade the overall confidence. Read the warnings card on the audit detail page or call GET /api/methodology/consensus/:auditId headlessly.

Cohort percentile. If your audit has a sector tag and at least one other audit shares it, we surface where this idea sits in the cohort distribution. GET /api/methodology/cohort/:auditId.

Calibration. The platform tracks outcomes you record and reports whether the score actually predicts funding events. Mean-funded vs mean-killed score, threshold accuracy, and a suggested GO threshold are exposed via GET /api/methodology/calibration. Aim for ≥30 outcomes before treating the discrimination number as load-bearing.

Which skills emit confidence

Lenses report a 0..1 confidence number alongside their pass/fail. The aggregator weights each lens by its confidence before deciding the overall verdict — a high-conviction fail outweighs a low-conviction pass elsewhere. Skills that currently emit confidence:

SkillConfidence drivers
audit-teamFounder LinkedIn match strength × number of corroborating mentions
audit-marketTAM source agreement (multi-source-tam) × CAGR confidence interval
audit-competitionNumber of distinct competitors found × evidence freshness
audit-financeComparable count × recency of comparable funding rounds
audit-tractionMetric verifiability (URLs / tweets / news) × stage match
audit-problem-solution-fitPain-point repetition across sources × intent-strength
audit-business-modelComparable monetization patterns × stage fit
audit-gtm-scaleChannel-test evidence × CAC/LTV plausibility