Stirling-Tools/Stirling-PDF

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173 of your 323 findings came from Repobility's proprietary detections. ✓ Repobility tags below mark them.

Upstream (GitHub) caused delay on this scan — not Repobility.

GitHub API rate-limited (HTTP 403) — preflight skipped, fell back to direct git clone.
Clone from GitHub took 106.44s for a 179.0 MB repo slow.
Repobility's analysis ran in 30.7s after the clone landed.

https://github.com/Stirling-Tools/Stirling-PDF · scanned 2026-06-05 07:26 UTC (1 week, 1 day ago) · 10 languages

4361 raw signals (281 security + 4080 graph) 11/13 scanners ran 56th percentile · Typescript · huge (>500K LoC) System graph score 53 (higher by 33)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 week, 1 day ago · v2 · 511 actionable findings from 2 signal sources. 1809 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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100.0% cov · 411 findings

Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	65.0	0.15	9.75
`security_score`	100.0	0.25	25.00
`testing_score`	80.0	0.20	16.00
`documentation_score`	95.0	0.15	14.25
`practices_score`	92.0	0.15	13.80
`code_quality`	73.0	0.10	7.30
Overall		1.00	86.1

security_score may be inflated — optional security scanners were skipped on this fast scan

Severity distribution — click a segment to filter

Active filters: search: "duplicates" × excluding tests × Reset all

Severity: Critical 54 High 50 Medium 46 Low 248 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 100 System graph 411 Crowd 0 Layer: Quality 167 Security 88 Cicd 9 Software 70 Frontend 111 Network 4 Hardware 5 Api 57

Exclude dismissed / FP Exclude test files

Scan summary Quality grade A- (86/100). Dimensions: security 100, maintainability 65. 281 findings (75 security). 510,008 lines analyzed.

Showing 0 of 511 actionable findings. 2320 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.

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