[daily-sentrux] Daily Sentrux Report - 2026-06-24

[github-actions[bot]]

This is the first baseline scan for the github/gh-aw repository — no prior history exists for trend comparison. The codebase scores 5222 / 10000 on overall quality signal, placing it in the moderate range. The primary bottleneck is complex_fn_count (968 complex functions), which is the main factor holding the score below 7000. Structural indicators are positive: coupling is very low (3.6%) and import cycles are minimal (2).

Quality Signal

Metric	Today	Yesterday	7d Trend
Overall	5222	—	—
Coupling Score	3.6%	—	—
Cycle Count	2	—	—
God File Count	2	—	—
Hotspot Count	0 ✅	—	—
Complex Fn Count	⚠️ 968	—	—
Max Depth	8	—	—

First run — no historical baseline available. Trends will appear in tomorrow's report.

Bottleneck

Current primary bottleneck: complex_fn_count — 968 functions exceed the complexity threshold across 5,467 analyzed files. High complexity in individual functions reduces testability, increases maintenance cost, and degrades the overall quality signal. Splitting long or deeply-nested functions into smaller, single-purpose helpers is the highest-leverage action available.

Rules

✅ All rules pass — Quality: 5222
(0 rules defined in .sentrux/rules.toml; rule definitions can be added to enforce architectural constraints)

Quality Trend (30 days)

This is the first recorded scan. Future runs will populate the 30-day trend chart here.

• Baseline date: 2026-06-24
• Baseline quality signal: 5222
• Files analyzed: 5,467 (of 5,519 tracked; 52 dropped — 49 by extension, 3 oversized)
• Import edges: 5,601 | Call edges: 3,916
• Cross-module edges: 2,943 of 5,601 total import edges (52.5%)

Recommendations

1. Reduce complex functions — 968 complex functions is the primary quality drag. Identify the highest-complexity files (likely concentrated in a few hotspot modules) and refactor long functions into focused helpers. Even a 20% reduction would meaningfully improve the quality signal.
2. Investigate and split god files — 2 god files are flagged. Large, all-encompassing files accumulate complexity over time and resist refactoring. Extract cohesive sub-modules from these files.
3. Resolve import cycles — 2 import cycles exist in the dependency graph. Eliminating them improves acyclicity and reduces hidden coupling. Introduce an abstraction layer or invert one dependency direction to break each cycle.

References:

• §28065933538

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• expires on Jun 26, 2026, 4:18 PM UTC-08:00

[github-actions[bot]]

Smoke ping: run 28068855925 checked in. ✅

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