/idea-scoring

name: idea-scoring
description: Aggregates all dimension scores into a final idea score (0–100) and issues a verdict. Implements a multiplicative-floor algorithm with Riskiest Assumption Test (RAT). The final output of every validation workflow.

<!-- version: 0.2.0 | outputs: memory/ideas/<slug>/scores.json -->

Skill: idea-scoring

Purpose

Produce a single, defensible verdict on an idea by aggregating all available dimension scores using a **multiplicative-floor algorithm** — a single catastrophic weakness kills the score, just like it kills a real startup. Includes a **Riskiest Assumption Test (RAT)** to convert the verdict into a concrete next action.

Input

• Idea slug
• One or more of the following (uses whatever is available):
• `memory/ideas/<slug>/idea.md`
• `memory/ideas/<slug>/desire_scores.json`
• `memory/ideas/<slug>/competitors.json`
• `memory/ideas/<slug>/pricing.json`
• `memory/ideas/<slug>/cac.json`
• `memory/ideas/<slug>/market_size.json`
• `memory/ideas/<slug>/distribution.json`
• `memory/ideas/<slug>/retention.json`
• `memory/ideas/<slug>/complexity.json`
• `memory/ideas/<slug>/weighted_signals.json`
• Optional: `memory/user_profile.md` (for founder-market fit)

Minimum Viable Input

At least **3 of 7 dimensions** must have source data. If fewer are available, refuse to score and list what's missing. Two dimensions are **mandatory** — Demand and Distribution. Without evidence of a real problem and a path to reach users, scoring is meaningless.

Scoring Dimensions

| Dimension | Weight | Source | What it measures | |---|---|---|---| | Demand | 20% | `desire_scores.json` + `weighted_signals.json` + `idea.md` | Real human desire + validated market signals | | Competition | 10% | `competitors.json` | Positioning gaps and defensibility | | Monetization | 20% | `pricing.json` + `cac.json` + `market_size.json` | Unit economics viability (LTV:CAC, WTP, market size) | | Distribution | 20% | `distribution.json` | Organic reach, paid viability, founder edge | | Retention | 15% | `retention.json` | Habit formation, churn risk, usage frequency | | Founder-Market Fit | 15% | `user_profile.md` + domain overlap with idea | Builder's edge, domain expertise, distribution advantage |

Dimension Score Mapping

Each dimension maps source data to a 0–100 sub-score using the rubrics below. When source data uses qualitative labels, apply these conversions.

Demand (0–100)

| Condition | Score range | |---|---| | `desire_strength_label` = "strong" AND trend_velocity = "rising-fast" | 80–100 | | `desire_strength_label` = "strong" OR trend_velocity = "rising" | 60–79 | | `desire_strength_label` = "moderate" AND some signal validation | 40–59 | | `desire_strength_label` = "weak" OR trend_velocity = "declining" | 15–39 | | No signal data, speculation only | 0–14 |

Adjust within range: +10 if cross-platform resonance confirmed, +5 if monetization_validated is true in `idea.md`.

Competition (0–100)

Higher = more favorable competitive landscape (counterintuitive — think of it as "opportunity score").

| Condition | Score range | |---|---| | `market_saturation` = "low", clear positioning gaps, no dominant incumbent | 75–100 | | `market_saturation` = "medium", 1–2 positioning gaps identified | 50–74 | | `market_saturation` = "high" but differentiation opportunities exist | 25–49 | | `market_saturation` = "high", no differentiation, dominant incumbents | 0–24 |

Adjust: +10 if top competitor complaints reveal an unserved pain point. -15 if a FAANG-class player owns the category.

Monetization (0–100)

| Condition | Score range | |---|---| | LTV:CAC ≥ 3:1 on at least 2 channels, WTP target ≥ $5/mo, viable SOM | 80–100 | | LTV:CAC ≥ 3:1 on 1 channel, WTP target ≥ $3/mo | 60–79 | | LTV:CAC ≥ 2:1, WTP target $1–$3/mo, marginal unit economics | 35–59 | | LTV:CAC < 2:1 OR viability_verdict = "not-viable" | 10–34 | | No pricing data or CAC data | 0–9 (flag as missing) |

Adjust: +10 if `freemium_conversion_estimate` > 5%. +5 if market_size_verdict = "large".

Distribution (0–100)

| Condition | Score range | |---|---| | `distribution_verdict` = "strong", viral_loop_exists = true | 80–100 | | `distribution_verdict` = "strong" OR (organic_reach = "high" + creator_economy_fit = "high") | 60–79 | | `distribution_verdict` = "moderate", at least one viable organic channel | 40–59 | | `distribution_verdict` = "weak", paid-only path | 15–39 | | No viable channel identified | 0–14 |

Adjust: +10 if founder has existing audience or distribution edge (from `user_profile.md`).

Retention (0–100)

| Condition | Score range | |---|---| | `retention_verdict` = "sticky", D30 ≥ 20%, habit_formation_score ≥ 4 | 80–100 | | `retention_verdict` = "sticky" OR D30 ≥ 15% | 60–79 | | `retention_verdict` = "moderate", D30 ≥ 8% | 40–59 | | `retention_verdict` = "disposable" OR D30 < 8% | 15–39 | | `churn_risk` = "high" AND no habit loop | 0–14 |

Adjust: +5 if natural_usage_frequency is daily. -10 if weekly-or-less with no external trigger.

Founder-Market Fit (0–100)

| Condition | Score range | |---|---| | Strong domain match in `strong_domains`, distribution advantages align, builder/growth tier | 75–100 | | Moderate domain overlap OR builder tier with adjacent experience | 50–74 | | Beginner tier but high motivation and time commitment (≥ 20 hrs/wk) | 30–49 | | No domain overlap, beginner tier, low time commitment | 0–29 |

If `user_profile.md` is unavailable, default to 50 (neutral) and flag as missing.

Scoring Algorithm

Step 1 — Compute dimension sub-scores

Apply the mapping rubrics above. Record each as `d_i` (0–100).

Step 2 — Apply floor penalty (the "Killer Dimension" rule)

Any dimension scoring below **25** is a potential startup killer. Apply this penalty:

floor_penalty = 1.0
for each dimension d_i:
    if d_i < 25:
        floor_penalty *= (d_i / 25)

This multiplicative penalty means a single catastrophic weakness (score 0–1