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vignesh2027/Vilvona-AI

https://github.com/vignesh2027/Vilvona-AI · scanned 2026-06-16 00:53 UTC (2 months, 1 week ago)

1632 raw signals (0 security + 1632 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 1 week ago · v1 · 1618 actionable findings from 1 signal source. 14 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 · 1618 findings

Severity distribution — click a segment to filter

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Severity: Critical 0 High 162 Medium 154 Low 827 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 1618 Crowd 0 Layer: Software 13 Frontend 162 Network 5 Hardware 6 Security 9 Cicd 5 Quality 1218 Api 200

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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 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 40 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.

12 matching findings on this repo

low Very large file: src/commands/doctor-legacy-config.migrations.test.ts (1752 lin…
low Very large file: src/commands/doctor/shared/legacy-config-migrate.test.ts (3151…
low Very large file: src/commands/doctor/shared/legacy-config-migrations.runtime.mo…
low Old/deprecated-named symbol `allowAnyValueForLegacy` in scripts/check-package-p…
low Old/deprecated-named symbol `cm_legacy` in scripts/e2e/commitments-safety-docke…
low Old/deprecated-named symbol `om_root_legacy` in extensions/feishu/src/bot.test.…
low Old/deprecated-named symbol `isLegacy` in extensions/whatsapp/src/accounts.what…
low Old/deprecated-named symbol `isLegacy` in extensions/whatsapp/src/accounts.ts:98
low Old/deprecated-named symbol `runtimeLegacy` in extensions/xai/src/tool-auth-sha…
low Old/deprecated-named symbol `migratedLegacy` in extensions/memory-core/src/drea…
low Old/deprecated-named symbol `listedLegacy` in extensions/memory-core/src/memory…
low Old/deprecated-named symbol `existingLegacy` in packages/memory-host-sdk/src/ho…

View all legacy markers findings →

Commented-out code 459 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 (5 lines) in test/proof/thinking-signature-real-proof.ts:29
info Commented-code block (5 lines) in ui/src/ui/app-scroll.ts:205
info Commented-code block (6 lines) in ui/src/ui/control-ui-auth.ts:10
info Commented-code block (6 lines) in ui/src/ui/markdown.ts:710
info Commented-code block (7 lines) in ui/src/ui/chat/run-lifecycle.ts:230
info Commented-code block (5 lines) in ui/src/ui/controllers/control-ui-bootstrap.ts…
info Commented-code block (5 lines) in ui/src/ui/views/overview-cards.ts:96
info Commented-code block (7 lines) in scripts/anthropic-prompt-probe.ts:3
info Commented-code block (6 lines) in scripts/update-clawtributors.ts:148
info Commented-code block (7 lines) in extensions/memory-lancedb/index.test.ts:3579
info Commented-code block (7 lines) in extensions/memory-lancedb/index.ts:204
info Commented-code block (6 lines) in extensions/google/vertex-adc.ts:322

View all commented-out code findings →

Config drift 60 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.

12 matching findings on this repo

low Possibly dead Python function: command_configure scripts/e2e/telegram-user-driver.py:513
low Stray `console.log` in TS/JS — test/vitest-unit-fast-config.test.ts:77
low Stray `console.log` in TS/JS — scripts/generate-base-config-schema.ts:20
low Stray `console.log` in TS/JS — scripts/generate-config-doc-baseline.ts:23
low Stray `console.log` in TS/JS — scripts/generate-bundled-channel-config-metadata…
low Very large file: ui/src/ui/views/config.ts (1909 lines)
low Very large file: extensions/codex/src/app-server/config.ts (1883 lines)
low Very large file: extensions/codex/src/app-server/config.test.ts (2159 lines)
low Very large file: src/config/config.plugin-validation.test.ts (1761 lines)
low Very large file: src/config/io.ts (2858 lines)
low Very large file: src/config/schema.help.ts (1981 lines)
low Very large file: src/config/validation.ts (1939 lines)

View all config drift findings →

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