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schoolie-nagayama-tech/school-management

https://github.com/schoolie-nagayama-tech/school-management · scanned 2026-06-16 00:04 UTC (2 months, 3 weeks ago)

213 raw signals (0 security + 213 graph)

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Complete repo analysis

Last scanned 2 months, 3 weeks ago · v1 · 210 actionable findings from 1 signal source. 3 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 · 210 findings

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Severity: Critical 1 High 1 Medium 95 Low 36 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 210 Crowd 0 Layer: Api 1 Frontend 84 Security 13 Cicd 2 Quality 110

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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.

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

medium Insecure pattern 'direct_innerhtml_assignment' in src/app/students/[studentId]/… src/app/students/[studentId]/progress/LegacyProgr…:390
low Very large file: src/app/students/[studentId]/progress/LegacyProgressPage.tsx (…

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Commented-out code 10 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/`.

10 matching findings on this repo

info Commented-code block (5 lines) in src/components/course-progress/CourseProgress…
info Commented-code block (6 lines) in src/components/proposals/ProposalEditor.tsx:2…
info Commented-code block (5 lines) in src/app/schedule/page.tsx:1590
info Commented-code block (7 lines) in src/app/api/webhooks/resend/route.ts:41
info Commented-code block (6 lines) in src/app/students/[studentId]/progress/NewProg…
info Commented-code block (5 lines) in src/app/courses/progress/mockup/page.tsx:270
info Commented-code block (9 lines) in src/lib/teacher-tier.ts:1
info Commented-code block (6 lines) in src/lib/api/schedule.ts:778
info Commented-code block (5 lines) in src/lib/api/seasonalCourses.ts:752
info Commented-code block (5 lines) in src/lib/api/pattern-matching.ts:253

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Config drift 2 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.

2 matching findings on this repo

medium Runtime service client appears to use placeholder configuration
high Agent instruction/config may expose a secret: .claude/settings.local.json .claude/settings.local.json:86

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