unilabsim/UniLab

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https://github.com/unilabsim/UniLab · scanned 2026-06-05 14:33 UTC (5 days, 4 hours ago) · 10 languages

423 raw signals (173 security + 250 graph) 11/13 scanners ran 96th percentile · Python · large (100-500K LoC) System graph score 79 (higher by 12)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 5 days, 4 hours ago · v2 · 162 actionable findings from 2 signal sources. 111 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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88.9% cov · 102 findings

Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	85.0	0.15	12.75
`security_score`	100.0	0.25	25.00
`testing_score`	100.0	0.20	20.00
`documentation_score`	100.0	0.15	15.00
`practices_score`	90.0	0.15	13.50
`code_quality`	45.0	0.10	4.50
Overall		1.00	90.8

security_score may be inflated — optional security scanners were skipped on this fast scan

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 2 High 36 Medium 11 Low 65 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 60 System graph 102 Crowd 0 Layer: Quality 89 Cicd 6 Software 29 Security 32 Api 1 Hardware 4 Frontend 1

Exclude dismissed / FP Exclude test files

Bug-class explainers. Each card groups findings of the same shape — these are the patterns most likely to ship to prod and reappear in future scans unless you systematically fix the cause, not just the instance.

Duplicates & near-duplicates 5 findings

What it is: Same function copy-pasted into multiple modules with minor variations.

Why it matters: Each copy drifts independently — bug fixes apply to one, miss the others.

How AI causes it: AI completes the same pattern in each file rather than refactoring to a shared helper.

Fix approach: Extract the duplicated logic into the most general module both call sites already import. Add tests at the helper level.

5 matching findings on this repo

low Near-duplicate function bodies in 2 places repo-level
low Near-duplicate function bodies in 7 places
low Near-duplicate function bodies in 9 places
low Near-duplicate function bodies in 12 places
low Near-duplicate function bodies in 3 places

View all duplicates & near-duplicates findings →

Legacy markers 2 findings

What it is: TODO, FIXME, XXX, HACK comments. Often indicate a known-broken path the author meant to fix.

Why it matters: Each marker is an unfinished thought. Production code shouldn't ship with debt that's documented but not tracked.

How AI causes it: AI mirrors the style of the codebase, so existing TODOs propagate into new code.

Fix approach: Convert each into a ticket. Delete the comment when the ticket lands. Use a pre-commit hook to block new TODOs without an issue link.

2 matching findings on this repo

high [MINED106] Phantom test coverage: test_g1_walk_flat_observation_construction_is… tests/envs/test_env_configs.py:167
low Old/deprecated-named symbol `model_50_legacy` in tests/training/test_resume_log…

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Commented-out code 9 findings

What it is: Lines of source that were intentionally disabled but never deleted.

Why it matters: Git already remembers history — commented code rots, becomes wrong, and adds noise to diffs.

How AI causes it: AI sometimes comments out broken code instead of fixing it. Reviewers approve out of inertia.

Fix approach: Delete. Trust `git log`. If you really need to remember, save it in a notes file under `docs/`.

9 matching findings on this repo

info Commented-code block (6 lines) in tests/base/test_sim_backend.py:973
info Commented-code block (9 lines) in scripts/deploy/sim_prototype.py:346
info Commented-code block (5 lines) in scripts/deploy/export_deploy_config.py:57
info Commented-code block (9 lines) in benchmark/benchmark_physics_step_isaacgym.py:…
info Commented-code block (5 lines) in benchmark/mjwarp/backend.py:264
info Commented-code block (5 lines) in src/unilab/base/backend/mujoco/xml.py:341
info Commented-code block (5 lines) in src/unilab/envs/motion_tracking/g1/tracking_o…
info Commented-code block (6 lines) in src/unilab/envs/locomotion/go2/handstand.py:2…
info Commented-code block (5 lines) in src/unilab/envs/locomotion/go2_arm/manip_loco…

View all commented-out code findings →

Config drift 3 findings

What it is: Settings duplicated across env files, Docker compose, K8s, and code defaults, all with slightly different values.

Why it matters: Production behaviour depends on whichever copy your loader reads first. Subtle bugs in staging that don't reproduce in dev.

How AI causes it: AI writes new config from memory rather than reading the existing source.

Fix approach: Pick one source of truth (env vars + a settings module). Have every other place import from there. Lint for duplicates in CI.

3 matching findings on this repo

high [MINED131] pre-commit hook `https://github.com/astral-sh/ruff-pre-commit` pinne… .pre-commit-config.yaml:2
low Very large file: tests/envs/test_env_configs.py (1981 lines)
info Commented-code block (5 lines) in scripts/deploy/export_deploy_config.py:57

View all config drift findings →

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