Gitlawb/openclaude

Public scan — anyone with this URL can view this analysis. Sign up to track your own repos privately, run scheduled re-scans, and get AI fix prompts via your dashboard.

Scan timing: clone 2.29s · analysis 33.51s · 22.7 MB · GitHub preflight 494ms

https://github.com/Gitlawb/openclaude · scanned 2026-05-31 01:22 UTC (5 days, 12 hours ago) · 10 languages

1461 findings (76 legacy + 1385 scanner) 10/13 scanners ran 61st percentile · Typescript · huge (>500K LoC) Scanner says 68 (higher by 18)

File as issue Image v2 schema

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 5 days, 12 hours ago · v2 · 776 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

JSON

100.0% cov · 700 gaps

Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	85.0	0.15	12.75
`security_score`	100.0	0.25	25.00
`testing_score`	74.0	0.20	14.80
`documentation_score`	100.0	0.15	15.00
`practices_score`	80.0	0.15	12.00
`code_quality`	69.0	0.10	6.90
Overall		1.00	86.5

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 5 High 18 Medium 21 Low 198 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 76 9-layer 700 Crowd 0 Layer: Quality 603 Software 61 Security 14 Cicd 2 Frontend 93 Hardware 3

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.

Fragile runtime 67 findings

What it is: Code that runs but breaks under predictable input — division by zero, missing keys, unbounded loops, off-by-one slicing.

Why it matters: Reaches production undetected because happy-path tests pass. First user with a weird input crashes the request.

How AI causes it: AI loves writing the happy path; doesn't probe edge cases unless explicitly asked.

Fix approach: Add property-based tests. Wrap external inputs with explicit validators. Use the framework's typed deserializer (Pydantic, attrs).

12 matching findings on this repo

medium [MINED111] Bare except continues silently: Bare `except:` (or `except Exception… python/atomic_chat_provider.py:35
medium [MINED111] Bare except continues silently: Bare `except:` (or `except Exception… python/ollama_provider.py:30
medium React interval is created without an explicit cleanup src/cli/print.ts:549
medium [SEC136] AI-typical over-broad exception handler swallowing all errors: Catch-a… src/utils/storage/SQLiteProvider.ts:257
medium [SEC134] AI scaffold leftover — Lorem ipsum / example.com / John Doe in code: L… src/utils/mcp/elicitationValidation.ts:24
medium [ERR002] Empty Catch Block: Empty catch blocks hide errors. src/components/Onboarding.tsx:167
medium [ERR002] Empty Catch Block: Empty catch blocks hide errors. src/commands/rename/rename.ts:71
medium [COMP001] High cognitive complexity: Function `atomic_chat_stream` has cognitiv… python/atomic_chat_provider.py:94
medium Public web service has no security.txt .well-known/security.txt
medium Public web app has no Content Security Policy index.html
medium [ERR002] Empty Catch Block: Empty catch blocks hide errors. src/bridge/replBridgeHandle.ts:22
medium React interval is created without an explicit cleanup src/components/Spinner/useShimmerAnimation.ts:13

View all fragile runtime findings →

Legacy markers 24 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 Legacy-named symbol `tengu_otk_slot_v1` in src/query.ts:1335
low Legacy-named symbol `provider_old` in src/commands/provider/provider.test.tsx:5…
low Legacy-named symbol `profile_old` in src/commands/onboard-github/onboard-github…
low Legacy-named symbol `tengu_copy` in src/commands/copy/copy.tsx:194
low Legacy-named symbol `hint_v2` in src/screens/REPL.tsx:4128
low Legacy-named symbol `has_backup` in src/utils/config.ts:1596
low Legacy-named symbol `no_backup` in src/utils/appleTerminalBackup.ts:75
low Legacy-named symbol `no_backup` in src/utils/iTermBackup.ts:36
low Legacy-named symbol `unlinkIfOld` in src/utils/cleanup.ts:134
low Legacy-named symbol `acct_old` in src/utils/codexCredentials.test.ts:227
low Legacy-named symbol `isDeprecated` in src/utils/model/deprecation.ts:10
low Legacy-named symbol `resolvedOld` in src/utils/plugins/marketplaceManager.ts:18…

View all legacy markers findings →

Commented-out code 445 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 (6 lines) in scripts/feature-flags-source-guard.test.ts:5
info Commented-code block (6 lines) in scripts/build.ts:64
info Commented-code block (6 lines) in src/interactiveHelpers.tsx:131
info Commented-code block (9 lines) in src/query.ts:322
info Commented-code block (5 lines) in src/QueryEngine.ts:196
info Commented-code block (8 lines) in src/tools.ts:351
info Commented-code block (5 lines) in src/Tool.ts:791
info Commented-code block (8 lines) in src/main.tsx:1
info Commented-code block (5 lines) in src/setup.ts:90
info Commented-code block (7 lines) in src/cost-tracker.ts:317
info Commented-code block (7 lines) in src/integrations/descriptors.ts:214
info Commented-code block (5 lines) in src/integrations/models/gpt.ts:32

View all commented-out code findings →

Config drift 22 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

high [MINED108] `self.is_configured` used but never assigned in __init__: Method `sc… python/smart_router.py:75
high [MINED108] `self.api_key` used but never assigned in __init__: Method `is_confi… python/smart_router.py:62
low File has no detected symbols: web/vite.config.ts
info TODO/FIXME marker in shipping code — src/utils/config.ts:177
info TODO/FIXME marker in shipping code — src/components/Settings/Config.tsx:264
low Very large file: src/utils/config.ts (1918 lines)
low Very large file: src/components/Settings/Config.tsx (1874 lines)
low Very large file: src/services/mcp/config.ts (1578 lines)
low Legacy-named symbol `has_backup` in src/utils/config.ts:1596
info Commented-code block (6 lines) in src/utils/config.ts:446
info Commented-code block (5 lines) in src/utils/cronJitterConfig.ts:19
info Commented-code block (6 lines) in src/utils/markdownConfigLoader.ts:258

View all config drift findings →

For AI agents: Voting guide (TP/FP) MCP manifest Stdio wrapper SARIF Integrate Findings queue Vote TP/FP on findings to calibrate the engine.

For AI agents + API integrations

Email me when this repo regresses

Free. We re-scan periodically; new criticals → your inbox. No signup required for the scan itself.

API access

This page is publicly accessible at: https://repobility.com/scan/a75ab839-80fb-497b-bd17-48a725fff0cb/

To check status programmatically (no auth required):

curl -s https://repobility.com/api/v1/public/scan/a75ab839-80fb-497b-bd17-48a725fff0cb/

Important — please don't re-submit the same URL repeatedly. The submission endpoint is idempotent: re-submitting the same git URL returns this same scan_token, not a new one. To re-scan this repo, sign up free and use the dashboard.