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karthik-valmiki / vero_safeguard

javascriptmain20508fe11.1K linessynced 1mo ago

Code health

8.1out of 10Excellent

This codebase scores 8.1 out of 10 on defect risk, which we rate excellent. It also scores maintainability 7.7 and static performance risk 9.8 out of 10. The three are scored separately and never blended into one number. The files you change most are the weak spot: 3 of 73 files are git hotspots, and they average 6.0.

Full health report →
Dead code41exportsUnused exports that nothing in the graph reaches
Lines of code
11.1K
Files
73
Symbols
349
Modules
18
Languages
6

Recent activity

All commits →

Commits

No commits indexed yet.

Decisions

  • Inline SVG to avoid an image request. Colours (#E84D31, #1A237E) are NPCI brand spec.proposed
  • Register.jsx — DPDP 2023-compliant 5-phase onboarding Collects rider data before showing consent scrproposed
  • We use a relatively small architecture so training is fast (demo purposes)proposed
  • Only serializable primitives are passed to the background task. The task opens its own SQLAlchemy seproposed
  • Evaluate each policy independently. A single bad row must never abort payouts for the rest of the zoproposed
  • Distribute total payout across intervals with equal slices. The last interval uses the exact remaindproposed

Needs attention

63 open
  • medium severity. ProposedInline SVG to avoid an image request. Colours (#E84D31, #1A237E) are NPCI brand spec.Auto-proposed decision awaiting review
  • medium severity. ProposedRegister.jsx — DPDP 2023-compliant 5-phase onboarding Collects rider data before showing consent scrAuto-proposed decision awaiting review
  • medium severity. ProposedWe use a relatively small architecture so training is fast (demo purposes)Auto-proposed decision awaiting review
  • medium severity. ProposedOnly serializable primitives are passed to the background task. The task opens its own SQLAlchemy seAuto-proposed decision awaiting review
  • medium severity. ProposedEvaluate each policy independently. A single bad row must never abort payouts for the rest of the zoAuto-proposed decision awaiting review

Where the risk concentrates

All 3 hotspots →

Ranked by prior bug fixes and change frequency, mined from full git history rather than from the code alone.

FileChurnPrior fixesMaintainersCommits 90d
dashboards.pybackend/app/routers98.4th01bus factor 13
payout_engine.pybackend/app/services95.3th01bus factor 13
AnalyticsTab.jsxadmin-dashboard/src/components/admin82.8th01bus factor 14

Composition

Open the graph →
javascript 52%python 36%markdown 4%dockerfile 4%json 3%Other 1%

Explore this codebase

  • Docs0 pages across 18 modules→
  • ChatAsk this codebase a question and get an answer with its sources→
  • Files73 files with per-file docs, health and history→
  • ArchitectureDependency graph, layers, and 5 entry points→
  • Code healthPer-file scores, 189 open findings, coverage and refactoring targets→
  • Knowledge graphEntities, communities, and the paths between them→
  • Change couplingFiles that keep changing together, mined from commit history→
  • CommitsChange-risk ranked history with agent provenance→
  • ContributorsBus factor, per-file maintainers, and the human/agent split→
  • StatsSize class, origin, lifetime churn, rhythm and records→
  • CostsWhat indexing this snapshot cost, by model and by run→