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tiennguyentt/knowledge-engine

https://github.com/tiennguyentt/knowledge-engine · scanned 2026-06-16 00:36 UTC (2 months, 2 weeks ago)

34 raw signals (23 security + 11 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 2 weeks ago · v1 · 16 actionable findings from 2 signal sources. 30 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
98.7
/100
Security checks
99
5 findings
System graph
99
77.8% cov · 11 findings
Critical
1
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Agents
10
0 votes
Crowd
0
reported
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 1 High 2 Medium 5 Low 6 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 5 System graph 11 Crowd 0 Layer: Quality 11 Security 2 Software 2 Frontend 1
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Scan summary Repository scanned at 98.7/100 with 77.8% coverage. It contains 224 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 11 findings — concentrated in quality (7), software (2), frontend (1). Risk profile is low: 0 critical, 0 high, 3 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 14 of 16 actionable findings. 46 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 security auth conf 0.78 2 occurrences Foundry mined security auth guardrail gaps: tiennguyentt/knowledge-engine
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…
2 occurrences
repo-level (2 hits)
high Security checks quality Quality conf 0.76 Foundry mined schema ui api mismatch: tiennguyentt/knowledge-engine
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: supported_by_verification_signal Repo…
high Security checks quality Testing conf 0.78 2 occurrences Foundry mined test ci gap after feedback: tiennguyentt/knowledge-engine
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)
medium Security checks quality Practices conf 0.62 12 occurrences Foundry mined assumption checks: tiennguyentt/knowledge-engine
Comment chain pattern product: assumption_checks Repo: tiennguyentt/knowledge-engine Thread: tiennguyentt/knowledge-engine#9 Outcome: ambiguous_needs_more_evidence Thread label: thread_needs_classification Source graph label: source_artifact_without_verification_graph Reasons: source_graph_has_real…
12 occurrences
repo-level (12 hits)
medium Security checks quality maintenance conf 0.70 18 occurrences Foundry mined blueprint gap alignment: tiennguyentt/knowledge-engine
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: …
18 occurrences
repo-level (18 hits)
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 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
medium System graph quality Tests conf 1.00 Very low test-to-source ratio
2 test file(s) for 21 source file(s) (ratio 0.10). Consider adding integration or unit tests for critical paths.
Coverage
low System graph quality Integrity conf 1.00 Old/deprecated-named symbol `model_copy` in app.py:1133
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 quality Integrity conf 1.00 Old/deprecated-named symbol `model_copy` in engine/pipeline.py:151
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: bubble
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
theme.py:485
low System graph software Dead code conf 1.00 Possibly dead Python function: render_playback
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
app.py:457
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 quality Complexity conf 1.00 Very large file: app.py (1524 lines)
Files with >800 lines often hide complexity hotspots and discourage tests.
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