RuleStack

Configs

Stacks

Compare

Diff

RuleStack

Configs

Stacks

Compare

Diff

Read API

RuleStack

Configs

Stacks

Compare

Diff

Read API

Diff/aledon8-openleukemia-ml-training-claude ↔ aledon8-openleukemia-cursor-rules-ml

Comparison

A · CLAUDE.md · Aledon8/OpenLeukemiaB · Cursor rules · Aledon8/OpenLeukemia
What each file covers, counted
DimensionSharedOnly in AOnly in BOverlap
Sections0110%
Commands000—
Section tags0210%

What each file covers

Sections

0 shared · 1 only in A · 1 only in B
  • − ML Training Memory
  • + ML Rules

Commands

neither file has any

Section tags

0 shared · 2 only in A · 1 only in B
  • − code-style
  • − performance
  • + do-not

Line diff

+12 added−6 removed3 unchanged20.0% identical
Aledon8/OpenLeukemia · ml/training/CLAUDE.md
@@ −1 @@
1# ML Training Memory
 
 
 
 
 
2 
3Apply this inside `ml/training/`.
4 
5- Prefer reproducible training scripts with explicit inputs, seeds, outputs, and metrics.
6- Keep patient-identifying data out of the repository.
7- Document label assumptions and cohort limitations near the training code.
8- Structured models support signals and trends, not diagnosis.
 
9 
Aledon8/OpenLeukemia · .cursor/rules/ml.mdc
@@ +1 @@
1---
2description: ML workspace rules
3globs:
4 - "ml/**/*"
5alwaysApply: false
6---
7 
8# ML Rules
9 
10- Keep structured ML workflows separate from LLM explanation workflows.
11- Use measurable criteria: split, metric, threshold, calibration, and known failure modes.
12- Do not commit patient-identifying or sensitive medical data.
13- Model outputs support signals and trends, not diagnosis or treatment guidance.
14- Document label assumptions, cohort limitations, and evaluation caveats near relevant code or reports.
15 
@@ −1 +1 @@
1−# ML Training Memory
1+---
2+description: ML workspace rules
3+globs:
4+ - "ml/**/*"
5+alwaysApply: false
6+---
27  
3−Apply this inside `ml/training/`.
8+# ML Rules
49  
5−- Prefer reproducible training scripts with explicit inputs, seeds, outputs, and metrics.
6−- Keep patient-identifying data out of the repository.
7−- Document label assumptions and cohort limitations near the training code.
8−- Structured models support signals and trends, not diagnosis.
10+- Keep structured ML workflows separate from LLM explanation workflows.
11+- Use measurable criteria: split, metric, threshold, calibration, and known failure modes.
12+- Do not commit patient-identifying or sensitive medical data.
13+- Model outputs support signals and trends, not diagnosis or treatment guidance.
14+- Document label assumptions, cohort limitations, and evaluation caveats near relevant code or reports.
915  
RuleStack

Built by

Kynth Studio

Directory

Configs
Stacks
Compare formats
Diff two configs
Best AGENTS.md examples

Formats

AGENTS.md
CLAUDE.md
Cursor rules
Copilot instructions

Reference

Read API
Corpus health
Privacy Policy
Terms

RuleStack

RuleStack

Built by

Kynth Studio

Directory

Configs
Stacks
Compare formats
Diff two configs
Best AGENTS.md examples

Formats

AGENTS.md
CLAUDE.md
Cursor rules
Copilot instructions

Reference

Read API
Corpus health
Privacy Policy
Terms

RuleStack

RuleStack

Built by

Kynth Studio

Directory

Configs
Stacks
Compare formats
Diff two configs
Best AGENTS.md examples

Formats

AGENTS.md
CLAUDE.md
Cursor rules
Copilot instructions

Reference

Read API
Corpus health
Privacy Policy
Terms

RuleStack