Code Understanding & Prescriptive Improvement Diagnostics

Measured trust, turning static analysis into a product.

CUPID scans an entire repository and returns a prioritised, line-located, prescriptive list of improvements: where the problem is, why it carries a cost and how to fix it, evidenced by real fixes from respected open-source projects.

CUPID ranks only what it can explain, measure, and defend.
BET 01 · RULE-FIRST, TOKEN-FREE

Zero LLM, from detection to wording

Conclusions, ranking, even the report wording all come from static rules, the IR, dependency graphs and version history; no model call sits anywhere on the product path. Scans are cheap, reproducible run to run, and the source never leaves the machine.
BET 02 · HISTORY-VALIDATED

Trajectories, not snapshots

A single snapshot cannot tell essential complexity from accidental complexity. CUPID uses cross-release trajectories to prove which problems really get fixed, and cites how others fixed them.
BET 03 · ONE NEUTRAL IR

Languages and rules fully decoupled

Every language first lowers into one neutral fact model, and rules read only facts. A new language is one new frontend; the product grows by addition, never by rewrite.
localized · pinned to file / function / lineprescriptive · says how to fix, not just labelsgrounded · cites real gold-repo fixesrule-first · zero tokens at scan scalehistory-validated · backed by 15 open-source histories
CUPID is customer-facing: it judges a repo's present and prescribes maintainability / performance / readability / architecture fixes · JaredMind is the internal sister system: it analyses authors and commit diffs; a clean division of labour · Python / C / C++ · 2026-07