Choose what to get done
Score a business document on the eight S's of strong writing
A completed eight-S audit register with exactly one scored row per required feature, each row carrying a rating, a verbatim text excerpt, and (when below threshold) a remediation note, plus a weighted total that is arithmetically consistent.
Score a content piece on the STEPPS virality framework
The buyer gets a complete STEPPS scorecard: all six factors (social currency, triggers, emotion, public, practical value, stories) rated as whole numbers on the agreed scale, each with a written rationale that clears a minimum word count, plus a total_score that equals the sum of the six scores.
Score a set of OKRs (0.0-1.0) and run the six classic-trap litmus checks
You get your OKR set scored on the 0.0-1.0 scale (each objective = the average of its key-result completion rates), each objective color-banded on the Google red/yellow/green scale, and a structural pass/fail against the six classic OKR-writing traps.
Score a term sheet's economic terms clause-by-clause
A structured JSON scorecard that classifies every required economic clause of the term sheet onto a three-tier favorability scale and computes a weighted founder-friendliness index.
Score AI model process and tool maturity into bands
A team assessing whether an AI model is mature enough to sell as a service gets a process-maturity band and a tool/system-maturity band computed directly from per-phase level scores, ready to feed the AIaaS feasibility decision.
Score an AI idea's business feasibility on 1-4 scales
A founder comparing AI product ideas gets a defensible 1-4 score on each business-feasibility dimension and an average, derived from concrete inputs (SOM, usage cadence, validation %, scalability), so ideas can be ranked on a like-for-like basis.
Score and rank candidate pricing metrics on the six-criteria rubric
I get a filled scorecard where every candidate metric is rated 1-5 on all six criteria with a weighted total and a clear rank order, so I can pick the key pricing variable defensibly.
Score and rank causes by importance, tractability, neglectedness
A function that takes a list of candidate causes each rated on importance (scale/severity), tractability (feasibility of progress), and neglectedness (how underfunded), and returns each cause's composite priority score plus a stable descending rank.
Score Problem Candidates on the Ikigai Four-Lens Fit
A founder receives a structured four-lens score for each candidate problem and a shortlist of those that clear every lens, so they pick a problem to focus on rather than a buzzword.
Scored brickyard inventory of demand-and-trust touchpoints
I get a structured brickyard: every brick sorted into the five areas (online presence, content, offerings, ecosystem, internal team), scored on the three fixed dimensions, with a ready/cracked/missing status per brick and per-area counts that match the bricks, ready to assemble into a journey.
Screen Startup Against Incubator/Accelerator Eligibility Criteria
A founder receives a structured eligibility screen showing, criterion by criterion, whether the startup meets a given incubator or accelerator program's stated rules and whether it clears the overall must-have gate.
SETDA AI Outcome Discovery Register
A product team running AI discovery gets a structured register of candidate AI outcomes, each correctly categorized (revenue / cost / risk) and mapped to a Sense/Explain/Think/Decide/Act method, with needs and requirements broken out per the SETDA framework.