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arch-team/ai-studio-project

https://github.com/arch-team/ai-studio-project · scanned 2026-06-17 01:35 UTC (1 month, 2 weeks ago)

156 raw signals (0 security + 156 graph)

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Complete repo analysis

Last scanned 1 month, 2 weeks ago · v2 · last Δ -18.4 (diff) · 93 actionable findings from 1 signal source. 63 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 · 93 findings

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Active filters: excluding tests × Reset all

Severity: Critical 1 High 17 Medium 43 Low 28 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 93 Crowd 0 Layer: Software 2 Frontend 6 Network 15 Hardware 4 Security 23 Cicd 3 Quality 40

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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.

Duplicates & near-duplicates 2 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.

2 matching findings on this repo

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

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Commented-out code 4 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/`.

4 matching findings on this repo

info Commented-code block (5 lines) in backend/tests/integration/contracts/test_api_…
info Commented-code block (7 lines) in backend/src/modules/datasets/__init__.py:20
info Commented-code block (7 lines) in infrastructure/cdk/stacks/compute/eks_stack.p…
info Commented-code block (5 lines) in frontend/e2e/audit/routes-manifest.ts:350

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Config drift 8 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.

8 matching findings on this repo

high Agent instruction/config may expose a secret: infrastructure/cdk/.claude/rules/… infrastructure/cdk/.claude/rules/construct-design…:34
medium Agent authority lacks a verifier contract: infrastructure/cdk/.claude/rules/con… infrastructure/cdk/.claude/rules/configuration.md
high Agent instruction/config may expose a secret: infrastructure/cdk/.claude/rules/… infrastructure/cdk/.claude/rules/testing.md:94
high Agent instruction/config may expose a secret: infrastructure/cdk/.claude/rules/… infrastructure/cdk/.claude/rules/architecture.md:23
high Agent instruction/config may expose a secret: frontend/.claude/rules/security.md frontend/.claude/rules/security.md:127
high Agent instruction/config may expose a secret: frontend/.claude/rules/interactio… frontend/.claude/rules/interaction-states.md:274
high Agent instruction/config may expose a secret: frontend/.claude/rules/state-mana… frontend/.claude/rules/state-management.md:62
high Agent instruction/config may expose a secret: .claude/plans/aws-deploy-e2e.md .claude/plans/aws-deploy-e2e.md:15

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