| Dimension | Shared | Only in A | Only in B | Overlap |
|---|---|---|---|---|
| Sections | 0 | 2 | 1 | 0% |
| Commands | 0 | 0 | 3 | 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
- + AI Service Rules
Commands
0 shared · 0 only in A · 3 only in B- + python -m mypy app
- + python -m ruff check .
- + python -m pytest
Section tags
1 shared · 3 only in A · 2 only in B- − code-style
- − monorepo
- − agent-behaviour
- + test
- + lint-format
- do-not
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 · .cursor/rules/ai-service.mdc
@@ +1 @@
1---
2description: Python FastAPI AI-service rules
3globs:
4 - "ai-service/**/*.py"
5alwaysApply: false
6---
7
8# AI Service Rules
9
10- Keep FastAPI route handlers thin; put reusable behavior in `app/domains`.
11- Use explicit Pydantic request and response models.
12- Preserve strict typing and keep `python -m mypy app` clean.
13- Use `response_model` for route outputs.
14- Treat extraction and model outputs as explainable signals or candidate data, not clinical decisions.
15- Run `python -m ruff check .` and relevant `python -m pytest` tests for Python changes.
16
@@ −1 +1 @@
1−# ML Workspace Instructions
1+---
2+description: Python FastAPI AI-service rules
3+globs:
4+ - "ai-service/**/*.py"
5+alwaysApply: false
6+---
27
3−This directory is for training pipelines, inference experiments, evaluations, and notebooks.
8+# AI Service Rules
49
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.
10+- Keep FastAPI route handlers thin; put reusable behavior in `app/domains`.
11+- Use explicit Pydantic request and response models.
12+- Preserve strict typing and keep `python -m mypy app` clean.
13+- Use `response_model` for route outputs.
14+- Treat extraction and model outputs as explainable signals or candidate data, not clinical decisions.
15+- Run `python -m ruff check .` and relevant `python -m pytest` tests for Python changes.
1316
