baneeishaque / RNN-SM
yamlmaster76cafe4756 linessynced 1d ago
Code health
9.1out of 10Excellent
This codebase scores 9.1 out of 10 on defect risk, which we rate excellent. It also scores maintainability 9.4 and static performance risk 9.8 out of 10. The three are scored separately and never blended into one number.
- Lines of code
- 756
Recent activity
All commitsCommits
No commits indexed yet.
Decisions
No decisions extracted yet.
Needs attention
6 open- medium severity. Knowledge siloalgorithms/prepareDataset.bash100% single-owner concentration
- medium severity. Knowledge siloreCreateCondaEnv.bash100% single-owner concentration
- low severity. Dead codealgorithms/IDC.pySafe to delete (40 lines)
- low severity. Dead codealgorithms/SS_QCCN.pySafe to delete (50 lines)
- low severity. Dead codealgorithms/full_RNN_SM.pySafe to delete (80 lines)
Composition
Open the graphyaml 42%python 33%shell 17%markdown 8%
Explore this codebase
- Docs13 pages across 2 modules
- ChatAsk this codebase a question and get an answer with its sources
- Files12 files with per-file docs, health and history
- ArchitectureDependency graph, layers, and 0 entry points
- Code healthPer-file scores, 17 open findings, coverage and refactoring targets
- Knowledge graphEntities, communities, and the paths between them
- Change couplingFiles that keep changing together, mined from commit history
- CommitsChange-risk ranked history with agent provenance
- ContributorsBus factor, per-file maintainers, and the human/agent split
- StatsSize class, origin, lifetime churn, rhythm and records
- CostsWhat indexing this snapshot cost, by model and by run