How do I interpret SonarQube code quality metrics to prove to management that our technical debt is actually costing us real money?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How do I interpret SonarQube code quality metrics to prove to management that our technical debt is actually costing us real money?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
SonarQube documentation metrics technical debt remediation effort maintainability rating code smells technical debt ratio Google ↗
SonarQube documentation measures coverage duplications complexity reliability security maintainability metrics Google ↗
- Understanding measures and metrics | SonarQube Server · docs.sonarsource.com
- Understanding measures and metrics | SonarQube Server 2025.4 LTA · docs.sonarsource.com
- Guide to Technical Debt Management | Reduce Debt | Sonar · sonarsource.com
- How to Measure Code Quality | Metrics & Methods · sonarsource.com
- Reduce & Manage Technical Debt with SonarQube | Sonar · sonarsource.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
SonarQube documentation metrics technical debt remediation effort maintainability rating code smells technical debt ratio OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
SonarQube documentation measures coverage duplications complexity reliability security maintainability metrics OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 |