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waledosunmu/worldcup-predictor

https://github.com/waledosunmu/worldcup-predictor · scanned 2026-06-16 00:54 UTC (2 months, 1 week ago)

21 raw signals (0 security + 21 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 1 week ago · v1 · 17 actionable findings from 1 signal source. 4 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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55.6% cov · 17 findings

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 0 Medium 5 Low 8 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 17 Crowd 0 Layer: Software 3 Frontend 1 Security 2 Cicd 1 Quality 10

Exclude dismissed / FP Exclude test files

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Scan summary Repository scanned at 76.8/100 with 55.6% coverage. It contains 372 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 21 findings — concentrated in quality (11), software (6), security (2). Risk profile is low: 0 critical, 0 high, 5 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 13 of 17 actionable findings. 21 raw detector signals were grouped into reader-sized issues. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

medium System graph quality Agent instructions conf 1.00 Agent instructions exist but release-hardening basics are missing

AI-coder instruction files were found, but the repo is missing license. Treat this as a contract gap: the agent is guided, but the generated output is not yet guarded by the controls that make it repeatable.

Repo hardeningGenerated repo pattern

medium System graph quality Placeholder conf 1.00 Critical user flow still appears backed by mock or placeholder data

A payment/auth/admin/order/billing-style flow contains mock, fake, TODO, dummy, or placeholder markers in runtime source. In the Fable corpus this is a high-leverage completeness smell: the app can look finished while the money, identity, or tenant flow is still scaffolded.

Mock dataCritical flowGenerated repo pattern

medium System graph cicd CI/CD security conf 1.00 GitHub Actions workflow grants broad write permissions

CI tokens with write permissions increase blast radius when an action, dependency, or PR workflow is compromised. Prefer job-level least-privilege permissions.

.github/workflows/daily-update.yml CI/CD securitySupply chainGithub actions

medium System graph security security conf 1.00 Insecure pattern 'direct_innerhtml_assignment' in docs/app.js:21

Found a known-risky pattern (direct_innerhtml_assignment). Review and replace if possible.

docs/app.js:21 Direct innerhtml assignment

medium System graph security Coverage conf 1.00 No auth library detected

The scanner did not find any standard auth library (JWT, OAuth, NextAuth, Auth0, etc.). The repo has auth/admin/session surface indicators, so auth may live in custom code, in a separate service, or be missing.

auth

low System graph quality Debug conf 1.00 Debug logging residue appears in source files

Found 61 console/debugger/print-style debug statements in non-test source. This is a common fast-generation residue before production cleanup.

CleanupRepo hardeningGenerated repo pattern

low System graph quality Integrity conf 1.00 2 occurrences Near-duplicate function bodies in 2 places

Functions with the same first-5-line body hash: scripts/run_tournament_backtest.py:overall_key, scripts/run_tournament_backtest.py:overall_key This is *the* AI-coder failure mode (4× more duplication in vibe-coded repos — see https://jw.hn/ai-code-hygiene). Consolidate or document why they're sepa…

2 occurrences

repo-level (2 hits)

duplicatesduplication

low System graph quality License conf 1.00 No license file detected

No LICENSE/COPYING/NOTICE file was found. Generated repositories often omit licensing, which blocks reuse and automated intake.

Repo hardeningGenerated repo pattern

low System graph quality Integrity conf 1.00 Old/deprecated-named symbol `simulate_group_legacy` in scripts/run_backtest.py:91

Names with suffixes like `_old`, `_v1`, `_deprecated` usually indicate replaced-but-not-removed code (typical AI-coder leftover). Confirm and delete, or rename if it's the active version.

old markerDead code

low System graph software Dead code conf 1.00 Possibly dead Python function: cluster_key

No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.

src/wcpred/simulate.py:125

low System graph software Dead code conf 1.00 4 occurrences Possibly dead Python function: nll

No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.

4 files, 4 locations

src/wcpred/calibration.py:83

src/wcpred/covariates.py:141

src/wcpred/dixoncoles.py:120

src/wcpred/goals.py:19

low System graph software Dead code conf 1.00 Possibly dead Python function: third_key

No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.

src/wcpred/simulate.py:188

low System graph quality Provenance conf 1.00 Shallow git history limits provenance confidence

The repository is a shallow clone. Origin/evolution analysis cannot distinguish fresh generation, imported legacy code, or long-lived human code with high confidence.

Git historyGenerated repo pattern

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