| Dimension | Shared | Only in A | Only in B | Overlap |
|---|---|---|---|---|
| Sections | 0 | 2 | 1 | 0% |
| Commands | 0 | 0 | 0 | — |
| Section tags | 1 | 3 | 2 | 17% |
What each file covers
Sections
0 shared · 2 only in A · 1 only in B- − ML Workspace Instructions
- − Rules
- + Documentation Page Memory
Commands
neither file has anySection tags
1 shared · 3 only in A · 2 only in B- − monorepo
- − do-not
- − agent-behaviour
- + performance
- + docs
- code-style
Line diff
Aledon8/OpenLeukemia · ml/CLAUDE.md
@@ −1 @@
1# ML Workspace Instructions
2
3This directory is for training pipelines, inference experiments, evaluations, and notebooks.
4
5## Rules
6
7- Keep structured ML workflows separate from LLM explanation workflows.
8- Prefer reproducible scripts and documented evaluation outputs over one-off notebook state.
9- Do not treat model output as diagnosis, urgent clinical judgment, or treatment recommendation.
10- Track assumptions about input data, labels, validation, and limitations close to the code or report that uses them.
11- Avoid committing patient-identifying or sensitive medical data.
12- Prefer measurable success criteria: metric, split, threshold, calibration, and known failure modes.
13
Aledon8/OpenLeukemia · frontend/src/features/documentation/CLAUDE.md
@@ +1 @@
1# Documentation Page Memory
2
3Apply this inside `frontend/src/features/documentation/`.
4
5- Keep project documentation readable for patients, contributors, and reviewers.
6- Link concepts back to charter, architecture, privacy, consent, and non-diagnostic AI behavior.
7- Avoid marketing-heavy copy; prefer precise product and safety language.
8- Preserve theme controls and accessible structure.
9
@@ −1 +1 @@
1−# ML Workspace Instructions
1+# Documentation Page Memory
22
3−This directory is for training pipelines, inference experiments, evaluations, and notebooks.
3+Apply this inside `frontend/src/features/documentation/`.
44
5−## Rules
6−
7−- Keep structured ML workflows separate from LLM explanation workflows.
8−- Prefer reproducible scripts and documented evaluation outputs over one-off notebook state.
9−- Do not treat model output as diagnosis, urgent clinical judgment, or treatment recommendation.
10−- Track assumptions about input data, labels, validation, and limitations close to the code or report that uses them.
11−- Avoid committing patient-identifying or sensitive medical data.
12−- Prefer measurable success criteria: metric, split, threshold, calibration, and known failure modes.
5+- Keep project documentation readable for patients, contributors, and reviewers.
6+- Link concepts back to charter, architecture, privacy, consent, and non-diagnostic AI behavior.
7+- Avoid marketing-heavy copy; prefer precise product and safety language.
8+- Preserve theme controls and accessible structure.
139
