Why it exists
The score is a shared, measurable quality signal. It makes quality comparable across documents and trackable over time, and it doubles as a CI gate: a score below 10 reports a violation, and a violation aterror severity exits non-zero and fails the run. A numeric signal is easier to act on than a binary pass/fail.
How it works
VectorLint scores a document with one of two methods, chosen by what the rule asks for.
Both methods report a score where 10 means the document fully meets the rule’s criteria and lower scores reflect more issues. Density scoring rewards documents where issues are rare relative to length; rubric scoring rewards documents that rate highly across the rubric’s criteria.
Density scoring is tunable per rule through strictness, a multiplier on error density. Rubric scoring is tuned through criterion weights in the rule’s frontmatter.
The formulas and worked examples live on the density scoring and rubric scoring pages.
Related
- How it works: the full review pipeline, from file discovery through scoring and reporting
- Strictness: control how strongly density scoring penalizes errors