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.

sport-analytics-org/court-training

https://github.com/sport-analytics-org/court-training · scanned 2026-06-16 00:19 UTC (2 months, 2 weeks ago)

37 raw signals (20 security + 17 graph)

File as issue Image

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 2 weeks ago · v1 · 23 actionable findings from 2 signal sources. 71 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON

88.9% cov · 15 findings

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 2 High 4 Medium 6 Low 9 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 8 System graph 15 Crowd 0 Layer: Quality 14 Security 2 Software 4 Frontend 1 Cicd 1 Api 1

Exclude dismissed / FP Exclude test files

Corpus Intelligence Cross-corpus context (cohort percentile, top patterns, fix plan) is shown only on repositories you own. Sign up and connect your repo to view it.

Scan summary Repository scanned at 95.5/100 with 88.9% coverage. It contains 181 nodes across 2 cross-layer flows, written primarily in mixed languages. Engine surfaced 17 findings — concentrated in quality (9), software (4), frontend (1). Risk profile is high: 0 critical, 1 high, 3 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 21 of 23 actionable findings. 94 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.

critical Security checks quality Practices conf 0.82 7 occurrences Foundry mined mock as real or placeholder: sport-analytics-org/court-training

Graph query export: Mock, sample, placeholder, or self-attested behavior treated as real Query id: mock_as_real_or_placeholder Query type: motif_query Intent: Hard negatives for fake completeness and missing real data paths. Motif: mock_as_real_or_placeholder Training usage: hard_negative Graph gol…

7 occurrences

repo-level (7 hits)

critical Security checks security auth conf 0.78 Foundry mined security auth guardrail gaps: sport-analytics-org/court-training

Graph query export: Security/auth changes without enough guardrails Query id: security_auth_guardrail_gaps Query type: motif_query Intent: Assumption-check security/auth examples requiring stronger tests or CI. Motif: security_auth_without_guardrails Training usage: assumption_check Graph gold labe…

high Security checks quality Practices conf 0.84 11 occurrences Foundry mined bad chains: sport-analytics-org/court-training

Comment chain pattern product: bad_chains Repo: sport-analytics-org/court-training Thread: sport-analytics-org/court-training#42 Outcome: not_resolved_or_not_observed Thread label: thread_has_human_issue_without_fix_context Source graph label: source_artifact_without_verification_graph Reasons: sou…

11 occurrences

repo-level (11 hits)

high Security checks quality Quality conf 0.76 Foundry mined schema ui api mismatch: sport-analytics-org/court-training

Graph query export: Schema, UI, and API mismatch Query id: schema_ui_api_mismatch Query type: motif_query Intent: Assumption-check examples for data-path consistency across layers. Motif: schema_ui_api_mismatch Training usage: assumption_check Graph gold label: assumption_check Repo: sport-analytic…

high Security checks quality Testing conf 0.78 2 occurrences Foundry mined test ci gap after feedback: sport-analytics-org/court-training

Graph query export: Feedback exposes missing tests or CI Query id: test_ci_gap_after_feedback Query type: motif_query Intent: Hard negatives for feedback/fix chains without adequate guardrails. Motif: test_ci_gap_after_feedback Training usage: hard_negative Graph gold label: weak_supervision_needs_…

2 occurrences

repo-level (2 hits)

high System graph security auth conf 1.00 FastAPI POST `predict` without auth dependency — src/court_training/api.py:107

`@router.post` decorator with no `Depends(get_current_user)` or auth-shaped dependency in its signature. Mutating endpoints should require authentication unless explicitly public.

src/court_training/api.py:107 securityAuth fastapi unauth mutation

medium Security checks quality Practices conf 0.62 31 occurrences Foundry mined assumption checks: sport-analytics-org/court-training

Comment chain pattern product: assumption_checks Repo: sport-analytics-org/court-training Thread: sport-analytics-org/court-training#9 Outcome: ambiguous_needs_more_evidence Thread label: thread_needs_classification Source graph label: source_artifact_without_verification_graph Reasons: source_grap…

31 occurrences

repo-level (31 hits)

medium Security checks quality maintenance conf 0.70 13 occurrences Foundry mined blueprint gap alignment: sport-analytics-org/court-training

Graph query export: Human feedback aligned with blueprint or architecture gaps Query id: blueprint_gap_alignment Query type: motif_query Intent: Curriculum-gap examples connecting issue threads to helicopter-view gaps. Motif: blueprint_gap_alignment Training usage: curriculum_gap Graph gold label: …

13 occurrences

repo-level (13 hits)

medium Security checks quality Practices conf 0.70 11 occurrences Foundry mined unresolved feedback: sport-analytics-org/court-training

Graph query export: Human feedback without linked fix evidence Query id: unresolved_feedback Query type: motif_query Intent: Negative/unresolved examples that should not be hallucinated into fixes. Motif: unlinked_feedback_needs_evidence Training usage: negative_or_unresolved Graph gold label: assu…

11 occurrences

repo-level (11 hits)

medium System graph quality Production readiness conf 1.00 Composite production-readiness gap

Multiple low-cost hardening controls are missing together: license, ci, tests. Opus verification showed these co-occurring gaps are a better readiness signal than reading each flag in isolation.

Repo hardeningGenerated repo pattern

medium System graph cicd CI/CD security conf 1.00 No CI/CD pipelines detected

No GitHub Actions, GitLab CI, or CircleCI configs found. Without CI you can't gate deploys on tests/lints.

CI/CD securityCoverage

medium System graph quality Tests conf 1.00 Very low test-to-source ratio

0 test file(s) for 23 source file(s) (ratio 0.00). Consider adding integration or unit tests for critical paths.

Coverage

low System graph quality Integrity conf 1.00 3 occurrences Near-duplicate function bodies in 2 places

Functions with the same first-5-line body hash: scripts/segmentation/train_basket.py:set_seed, scripts/detection/train_rfdetr.py:set_seed 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 separate.

3 occurrences

repo-level (3 hits)

duplicatesduplication

low System graph quality Integrity conf 1.00 Near-duplicate function bodies in 3 places

Functions with the same first-5-line body hash: src/court_training/segmentation/model.py:forward, src/court_training/segmentation/model.py:forward, src/court_training/segmentation/model.py:forward This is *the* AI-coder failure mode (4× more duplication in vibe-coded repos — see https://jw.hn/ai-c…

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 software Dead code conf 1.00 Possibly dead Python function: closure

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

src/court_training/homography.py:60

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

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

src/court_training/dataset.py:122

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

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

src/court_training/segmentation/model.py:155

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

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

src/court_training/detection/model.py:37

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

low System graph api Wiring conf 1.00 Unused endpoint: POST /predict

`src/court_training/api.py` declares `POST /predict` but no frontend code we scanned calls it. This is fine if the endpoint serves external clients (mobile app, third-party, server-side webhooks). Otherwise it's dead code — consider removing or documenting who consumes it.

Unused endpoint

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/12a284e8-a858-44c8-8517-de4ac23a964f/

To check status programmatically (no auth required):

curl -s https://repobility.com/api/v1/public/scan/12a284e8-a858-44c8-8517-de4ac23a964f/

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.