youngbryan97/aura

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https://github.com/youngbryan97/aura · scanned 2026-06-05 20:23 UTC (4 days, 13 hours ago) · 10 languages

1104 raw signals (160 security + 944 graph) 11/13 scanners ran 55th percentile · Python · medium (20-100K LoC) System graph score 60 (higher by 7)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 4 days, 13 hours ago · v2 · 504 actionable findings from 2 signal sources. 128 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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100.0% cov · 441 findings

Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	60.0	0.15	9.00
`security_score`	100.0	0.25	25.00
`testing_score`	23.0	0.20	4.60
`documentation_score`	74.0	0.15	11.10
`practices_score`	76.0	0.15	11.40
`code_quality`	59.0	0.10	5.90
Overall		1.00	67.0

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 0 High 72 Medium 14 Low 337 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 63 System graph 441 Crowd 0 Layer: Software 81 Quality 316 Security 37 Cicd 6 Frontend 1 Hardware 3 Api 60

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 1 finding

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.

1 matching finding on this repo

low Near-duplicate function bodies in 2 places repo-level

View all duplicates & near-duplicates findings →

Legacy markers 6 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.

6 matching findings on this repo

low Archive or legacy directory is mixed into the active repository root archive:1
low Old/deprecated-named symbol `_fake_legacy` in tests/test_web_search_research_pi…
low Old/deprecated-named symbol `FamilyLegacy` in core/identity/biography.py:17
low Old/deprecated-named symbol `FamilyLegacy` in core/brain/pii_scrubber.py:31
low Old/deprecated-named symbol `_self_repair_legacy` in core/skills/self_repair_le…
low Old/deprecated-named symbol `_self_repair_legacy` in skills/self_repair.py:2

View all legacy markers findings →

Commented-out code 63 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/`.

12 matching findings on this repo

info Commented-code block (10 lines) in aura_main.py:74
info Commented-code block (5 lines) in archive/migration_scripts/migrate_p1_silent_p…
info Commented-code block (7 lines) in interface/routes/chat.py:1858
info Commented-code block (5 lines) in tests/test_tier4_decisive.py:432
info Commented-code block (6 lines) in tests/test_null_hypothesis_defeat.py:145
info Commented-code block (7 lines) in tests/test_tier4_metacognition.py:188
info Commented-code block (5 lines) in tests/test_iit_behavioral.py:95
info Commented-code block (5 lines) in tests/phenomenal/test_supplementary.py:247
info Commented-code block (5 lines) in tests/phenomenal/test_battery.py:58
info Commented-code block (6 lines) in scripts/migrate_p1_io_concurrency.py:42
info Commented-code block (6 lines) in scripts/aura_task_ownership_codemod.py:4
info Commented-code block (6 lines) in scripts/generate_txt_export.py:12

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

low File has no detected symbols: interface/static/memory/vite.config.js
low File has no detected symbols: interface/static/shell/vite.config.js
info Commented-code block (7 lines) in core/config.py:188

View all config drift findings →

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