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youngbryan97/aura

https://github.com/youngbryan97/aura · scanned 2026-06-16 01:10 UTC (2 months, 1 week ago)

476 raw signals (0 security + 476 graph)

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Complete repo analysis

Last scanned 2 months, 1 week ago · v1 · 446 actionable findings from 1 signal source. 30 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 · 446 findings

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Severity: Critical 0 High 29 Medium 18 Low 303 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 446 Crowd 0 Layer: Software 25 Frontend 1 Hardware 3 Security 25 Cicd 3 Quality 329 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 7 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.

7 matching findings on this repo

low Old/deprecated-named symbol `_fake_legacy` in tests/test_web_search_research_pi…
low Old/deprecated-named symbol `ri_cpu_time_qos_legacy` in tools/memory_sentinel.p…
low Old/deprecated-named symbol `ri_cpu_time_qos_legacy` in core/utils/memory_monit…
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

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Commented-out code 95 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:78
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:3932
info Commented-code block (5 lines) in tests/test_tier4_decisive.py:432
info Commented-code block (5 lines) in tests/test_research_modules.py:322
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:187
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 (5 lines) in scripts/build_app.py:95
info Commented-code block (6 lines) in scripts/migrate_p1_io_concurrency.py:42

View all commented-out code findings →

Config drift 1 finding

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.

1 matching finding on this repo

info Commented-code block (7 lines) in core/config.py:188

View all config drift findings →

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