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Diff/aledon8-openleukemia-github-instructions-ml-instructions ↔ aledon8-openleukemia-cursor-rules-supabase

Comparison

A · Copilot instructions · Aledon8/OpenLeukemiaB · Cursor rules · Aledon8/OpenLeukemia
What each file covers, counted
DimensionSharedOnly in AOnly in BOverlap
Sections0110%
Commands000—
Section tags11050%

What each file covers

Sections

0 shared · 1 only in A · 1 only in B
  • − ML Instructions
  • + Supabase Rules

Commands

neither file has any

Section tags

1 shared · 1 only in A · 0 only in B
  • − agent-behaviour
  •   do-not

Line diff

+10 added−7 removed5 unchanged33.3% identical
Aledon8/OpenLeukemia · .github/instructions/ml.instructions.md
@@ −1 @@
1---
2applyTo: "ml/**/*"
 
 
 
3---
4 
5# ML Instructions
6 
7- Keep structured ML workflows separate from LLM explanation workflows.
8- Use measurable criteria: split, metric, threshold, calibration, and known failure modes.
9- Do not commit patient-identifying or sensitive medical data.
10- Model outputs support signals and trends, not diagnosis or treatment guidance.
11- Document label assumptions, cohort limitations, and evaluation caveats near the relevant code or report.
12 
Aledon8/OpenLeukemia · .cursor/rules/supabase.mdc
@@ +1 @@
1---
2description: Supabase data, storage, and RLS rules
3globs:
4 - "supabase/**/*"
5alwaysApply: false
6---
7 
8# Supabase Rules
9 
10- Use Supabase for auth, CRUD, storage, consent records, RLS, and lightweight Edge Functions.
11- Keep heavy ML, OCR, extraction, parsing, and model workflows in `ai-service`.
12- Treat RLS as a primary protection layer.
13- Pair sensitive tables with narrow, auditable policies.
14- Plan affected data flows and access paths before schema or policy changes.
15 
@@ −1 +1 @@
11 ---
2−applyTo: "ml/**/*"
2+description: Supabase data, storage, and RLS rules
3+globs:
4+ - "supabase/**/*"
5+alwaysApply: false
36 ---
47  
5−# ML Instructions
8+# Supabase Rules
69  
7−- Keep structured ML workflows separate from LLM explanation workflows.
8−- Use measurable criteria: split, metric, threshold, calibration, and known failure modes.
9−- Do not commit patient-identifying or sensitive medical data.
10−- Model outputs support signals and trends, not diagnosis or treatment guidance.
11−- Document label assumptions, cohort limitations, and evaluation caveats near the relevant code or report.
10+- Use Supabase for auth, CRUD, storage, consent records, RLS, and lightweight Edge Functions.
11+- Keep heavy ML, OCR, extraction, parsing, and model workflows in `ai-service`.
12+- Treat RLS as a primary protection layer.
13+- Pair sensitive tables with narrow, auditable policies.
14+- Plan affected data flows and access paths before schema or policy changes.
1215  
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