Dashboard
The rvue web dashboard lets you explore your team's intelligence, manage repositories, configure analysis, and monitor sync activity.
Access the dashboard at rvue.dev/dashboard after signing in with GitHub.
Repositories
The main dashboard page lists all repositories you've enabled with rvue. Each repo shows:
| Column | Description |
|---|---|
| Health grade | A/B/C/D grade derived from anti-pattern severity, maturity level, and convention coverage |
| Conventions | Number of coding conventions extracted |
| Issues | Anti-pattern count, with critical and high severity highlighted |
| Synced | Time since the last intelligence sync |
| Status | Repository status (active, error, syncing) |
Repositories are enabled via the CLI (rvue enable). The dashboard displays real data from the most recent analysis.
Intelligence Viewer
Click any repository to open the intelligence viewer. It has six tabs:
Overview
A summary of key metrics: total conventions, anti-patterns (with severity breakdown), knowledge areas, and mapped reviewers. The overview also shows:
- Intelligence sources: which data sources contributed (code analysis, PR analysis, config import, etc.)
- Convention coverage by category: bar chart showing how conventions are distributed across imports, testing, naming, etc.
- Needs attention: critical and high-severity anti-patterns surfaced prominently with recommended alternatives
Conventions
All coding conventions extracted from your codebase, grouped and searchable. Each convention shows:
- Category: imports, testing, naming, async, error-handling, security, etc.
- Confidence score: 0-100% derived from evidence frequency and source reliability
- Evidence count: how many files or PR comments support this convention
- Source: code analysis, PR analysis, config import, or stack baseline
- Examples: expandable code examples showing the convention in practice
Anti-Patterns
Patterns that get PRs rejected or introduce bugs, sorted by severity. Each anti-pattern includes:
- Severity: critical, high, medium, or low
- Why it's problematic: the reason this pattern should be avoided
- Correct approach: the recommended alternative
- Evidence: PR numbers and review excerpts where this pattern was flagged
Knowledge
Domain knowledge extracted from PR discussions, organized by topic (authentication, database, deployment, etc.). Each entry has a confidence score and source PR references. This captures tribal knowledge that normally lives only in people's heads.
Reviewers
Maps team members to their areas of expertise based on PR review patterns. Shows review count, approval rate, and expertise confidence per code area. Useful for suggesting reviewers on new PRs.
Risks
Risk factors identified from your PR history and codebase:
- Hot files: files changed frequently across many PRs (higher review scrutiny needed)
- Large PRs: PRs with 500+ lines changed (higher defect risk)
Repository Settings
Each repository has configurable analysis parameters accessible from the settings page:
| Setting | Default | Description |
|---|---|---|
| Auto-sync | Off | Automatically update intelligence when PRs are merged via GitHub Action |
| Include closed PRs | On | Analyze closed (not merged) PRs for anti-pattern detection |
| Lookback period | 12 months | How far back to analyze PR history |
| Min confidence | 70% | Conventions below this threshold are excluded |
| Min PRs for pattern | 10 | Require this many PRs before reporting a convention |
| Domain knowledge | On | Build a knowledge graph from PR discussions |
| Reviewer expertise | On | Map reviewers to their areas of expertise |
| Ignored patterns | node_modules/, dist/, ... | File patterns to exclude from analysis |
| Ignored authors | dependabot[bot], renovate[bot] | Authors to exclude from PR analysis |
ℹSettings persistence
Account
The account page shows your profile, plan, and usage statistics:
- Plan & usage: current plan, total repositories, PRs analyzed, conventions and anti-patterns across all repos
- Recent activity: last sync events with metadata (PRs processed, conventions extracted, analysis duration)
- API keys: generate, copy, and revoke API tokens for CLI and CI/CD
- Connected accounts: GitHub OAuth status
API key management
Generate API keys directly from the dashboard for use with the CLI or CI/CD pipelines. Tokens use the rvue_ prefix and are displayed only once at creation. Store them as repository secrets (e.g. RVUE_TOKEN) for automated workflows.