.vectorlint.ini is VectorLint’s project configuration file. It lives in your project root and controls three things: global behavior settings, where VectorLint looks for custom rules, and which rule packs run on which files.
Run vectorlint init to generate a starter file. You can edit it manually at any time.
Global Settings
These settings apply to all evaluations in the project.
| Setting | Type | Default | Description |
|---|
RulesPath | string | (none) | Root directory for custom rule packs. If omitted, only built-in presets are used. |
Concurrency | integer | 4 | Number of evaluations to run in parallel. |
DefaultSeverity | string | warning | Severity level for reported violations: warning or error. |
# .vectorlint.ini
RulesPath=.github/rules
Concurrency=4
DefaultSeverity=warning
File Pattern Sections
Use [glob/pattern] sections to map file types to rule packs. Each section targets files matching the pattern and specifies which rules to run.
[**/*.md]
RunRules=Acme
[content/docs/**/*.md]
RunRules=Acme
GrammarChecker.strictness=9
TechnicalAccuracy.threshold=8.0
[content/marketing/**/*.md]
RunRules=TechCorp
BrandVoice.strictness=8
[content/drafts/**/*.md]
RunRules=
RunRules
A comma-separated list of rule pack names. Pack names correspond to subdirectory names inside RulesPath.
Set RunRules= with no value to explicitly skip all rules for matching files (useful for drafts or generated content).
Rule Pack Directory Structure
The RulesPath setting defines where VectorLint looks for rule packs. Each subdirectory becomes an available pack name.
project/
├── .github/
│ └── rules/ ← RulesPath
│ ├── Acme/ ← Pack: "Acme"
│ │ ├── grammar.md
│ │ └── style.md
│ └── TechCorp/ ← Pack: "TechCorp"
│ └── brand.md
└── .vectorlint.ini
Acme/ are available when you set RunRules=Acme. Nesting is supported — you can organize rules into subdirectories within a pack.
Cascading Configuration
VectorLint applies configuration blocks from general to specific, similar to Vale’s cascade behavior. All blocks that match a given file are applied; more specific patterns override settings from more general ones, and rule packs accumulate.
# Applied first — general
[**/*.md]
RunRules=GeneralRules
Grammar.strictness=5
# Applied second — more specific
# Result: runs GeneralRules AND TechDocs; strictness is 9 (overrides 5)
[content/docs/**/*.md]
RunRules=TechDocs
Grammar.strictness=9
content/docs/**/*.md is more specific than **/*.md.
Strictness Overrides
You can tune how harshly individual check rules score content on a per-pattern basis.
[pattern]
RuleID.strictness=value
| Level | Value | Penalty per 1% error density | Typical use |
|---|
| Lenient | 1–3 | ~5 points | Drafts |
| Standard | 4–7 | ~10 points | General content |
| Strict | 8–10 | ~20 points | Technical documentation |
lenient, standard, strict) or direct numeric multipliers:
[content/docs/**/*.md]
RunRules=Acme
GrammarChecker.strictness=strict
TechnicalAccuracy.strictness=20
Complete Example
# .vectorlint.ini
RulesPath=.github/rules
Concurrency=4
DefaultSeverity=warning
# All markdown files — baseline checks
[**/*.md]
RunRules=Acme
GrammarChecker.strictness=5
# Technical docs — stricter standards
[content/docs/**/*.md]
RunRules=Acme
GrammarChecker.strictness=9
TechnicalAccuracy.threshold=8.0
# Marketing — brand voice rules
[content/marketing/**/*.md]
RunRules=TechCorp
BrandVoice.strictness=8
# Drafts — skip all checks
[content/drafts/**/*.md]
RunRules=
Global Style Guide (VECTORLINT.md)
In addition to .vectorlint.ini, you can place a VECTORLINT.md file in your project root to define global style instructions in plain language.
Zero-config mode: If no .vectorlint.ini exists, VectorLint automatically detects VECTORLINT.md, creates a synthetic “Style Guide Compliance” rule, and evaluates content against it.
Combined mode: When .vectorlint.ini is present, the contents of VECTORLINT.md are prepended to the system prompt for every evaluation — making your global tone and terminology preferences active across all rules.
Keep VECTORLINT.md concise. VectorLint emits a warning if the file exceeds approximately 4,000 tokens, as very large contexts can degrade evaluation quality and increase API costs.
Next Steps