x1xhlol/system-prompts-and-models-of-ai-tools

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x1xhlol/system-prompts-and-models-of-ai-tools

https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools · scanned 2026-06-05 04:50 UTC (9 hours, 54 minutes ago) · 10 languages

7 findings (1 legacy + 6 scanner) 78th percentile · Unknown · Scanner says 99 (lower by 26)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 9 hours, 54 minutes ago · v2 · 4 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

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Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	45.0	0.15	6.75
`security_score`	100.0	0.25	25.00
`testing_score`	70.0	0.20	14.00
`documentation_score`	60.0	0.15	9.00
`practices_score`	70.0	0.15	10.50
`code_quality`	80.0	0.10	8.00
Overall		1.00	73.2

Severity distribution — click a segment to filter

Active filters: layer: quality × excluding tests × Reset all

Severity: Critical 0 High 0 Medium 2 Low 0 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 1 9-layer 3 Crowd 0 Layer: Quality 1 Api 1 Frontend 1 Cicd 1

Exclude dismissed / FP Exclude test files

Scan summary Repository scanned at 98.9/100 with 66.7% coverage. It contains 49 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 3 findings — concentrated in api (1), frontend (1), cicd (1). Risk profile is low: 0 critical, 0 high, 1 medium. Recommended next step: open the api layer findings first — that's where the highest-impact wins live.

Showing 1 of 4 findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

medium Legacy quality practices conf 1.00 [CFG006] Missing .gitignore: No .gitignore file. Risk of committing secrets and build artifacts.

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practiceslegacy

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