| Dimension | Shared | Only in A | Only in B | Overlap |
|---|---|---|---|---|
| Sections | 0 | 1 | 1 | 0% |
| Commands | 0 | 0 | 0 | — |
| Section tags | 0 | 2 | 1 | 0% |
What each file covers
Sections
0 shared · 1 only in A · 1 only in B- − ML Instructions
- + ML Inference Memory
Commands
neither file has anySection tags
0 shared · 2 only in A · 1 only in B- − do-not
- − agent-behaviour
- + performance
Line diff
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 · ml/inference/CLAUDE.md
@@ +1 @@
1# ML Inference Memory
2
3Apply this inside `ml/inference/`.
4
5- Keep inference interfaces typed, deterministic, and easy to validate.
6- Return explainable scores or signals with limitations, not clinical conclusions.
7- Preserve compatibility with `ai-service/` consumers when inference code is promoted.
8- Validate feature order, units, and missing-value behavior explicitly.
9
@@ −1 +1 @@
1−---
2−applyTo: "ml/**/*"
3−---
1+# ML Inference Memory
42
5−# ML Instructions
3+Apply this inside `ml/inference/`.
64
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.
5+- Keep inference interfaces typed, deterministic, and easy to validate.
6+- Return explainable scores or signals with limitations, not clinical conclusions.
7+- Preserve compatibility with `ai-service/` consumers when inference code is promoted.
8+- Validate feature order, units, and missing-value behavior explicitly.
129
