Code Review Analytics

The Analytics section gives your team a data layer on top of every code review Oliver has run — surfacing where quality is improving, where findings cluster, and how individual contributors are trending over time. Access it from Code Review → Analytics in the navigation.

Analytics tabs

The Analytics section contains three tabs. The Leaderboard and Skill Matrix tabs are fully documented on their own reference pages; this page covers the Overview and Author Performance views.

Tab	What it shows
Overview	Period-over-period PR volume, average Quality Score, finding volume by severity, and top finding categories
Leaderboard	Developer scores ranked by quality and code complexity — see Leaderboard
Skill Matrix	Domain proficiency heatmap across Security, Performance, Correctness, and Patterns — see Skill Matrix

Overview tab

The Overview tab answers: Is our code quality improving? Which finding types appear most often?

Summary cards

Four metric cards appear at the top of the Overview tab:

Card	Description
PRs reviewed	Total pull requests that received a review in the selected period
Avg Quality Score	Mean quality score (1–10 scale) across all reviewed PRs; the score starts at 10 and is reduced by finding severity
Total findings	Sum of all findings, broken down by Critical, High, Medium, and Low severity
Resolution rate	Percentage of findings resolved before the PR was merged

Period comparison

Below the summary cards, weekly and monthly panels show current-period values alongside prior-period values with directional indicators (↑ / ↓). Read the combination of Quality Score and finding count together:

Quality Score	Finding count	Interpretation
↑ Rising	↓ Falling	Developers are catching and fixing issues earlier
↑ Rising	→ Stable	Team is resolving a larger share of findings before merge
↓ Falling	↑ Rising	New contributors, new repositories, or reduced resolution effort — check convention rules coverage
→ Stable	→ Stable	Review quality is holding steady — use the Leaderboard to check for uneven distribution across developers

Finding trend chart

The trend chart plots finding volume by severity (Critical, High, Medium, Low) over the selected date range. Each severity renders as a separate series.

Pattern	What it signals
Critical and High declining over weeks	Developers are addressing severe issues before merge
Medium and Low rising while High stays flat	Higher PR volume or new convention rules are surfacing more style issues — expected when you first add rules
Sudden spike across all severities	A large refactor landed, a new repository was added, or a new contributor joined the review pool
Flat across all severities	Coverage and quality are stable; widen the date range to spot longer trends

Top finding categories

Below the trend chart, a ranked list shows which finding categories appear most frequently — for example, “Missing error handling”, “Hardcoded secrets”, or “N+1 queries”. The top categories are the highest-yield targets for convention rules. A single convention file targeting a pattern that appears in 40% of your findings eliminates that noise from future reviews. See convention rules for how to encode these patterns.

Author performance tab

The Author Performance tab aggregates data across all reviewed pull requests, one row per developer. Use it alongside the Leaderboard for both relative team rankings and individual deep-dives.

Author table columns

Column	Description
PRs reviewed	Total PRs that received an AI review for this author in the selected period
Avg Quality Score	Mean quality score (1–10) across all of this author’s reviewed PRs
Total findings	Sum of findings by severity for this author
Resolution rate	Percentage of this author’s findings resolved before merge
Impact score	Cumulative code complexity contributed — see the Leaderboard for the exact formula

Developer profile dialog

Click any row to open the full profile. Profile data uses a rolling 90-day window regardless of the tab’s selected date range.

Section	Description
Profile header	Avatar, total MR count, total findings, average quality score, and overall Skill Matrix percentage
Skill Radar	Polar chart of the four Skill Matrix domains for this developer
Resolution Rate	Findings resolved before merge, displayed as a progress bar
Focus Areas	Auto-derived Strengths (top 2 domains) and Development areas (bottom 2 domains)
Weekly Findings Trend	Stacked column chart of findings by severity over the past 90 days
Pattern Force Graph	AI-identified recurring finding patterns visualized as a force-directed network

Use author profiles alongside the Leaderboard to get both relative team rankings and individual deep-dives.

Filters

All charts and tables respond to the filter bar at the top of the Analytics page:

Filter	Effect
Date range	Standard presets (7d, 30d, 90d) or a custom range
Repository	Limit data to one or more connected repositories
Severity	Surface only Critical and High to focus on the most impactful findings

Leaderboard

Scoring formula that balances code quality with productivity across your team

Skill Matrix

Domain-level proficiency heatmap across Security, Performance, Correctness, and Patterns

Convention rules

Encode team standards to reduce recurring findings in future reviews

Code Review

CostOps

Deep Response Engine

Infrastructure

ChatOps

Skills

Artifacts & Dashboards

Analytics tabs

Overview tab

Summary cards

Period comparison

Finding trend chart

Top finding categories

Author performance tab

Author table columns

Developer profile dialog

Filters

Leaderboard

Skill Matrix

Convention rules

​Analytics tabs

​Overview tab

​Summary cards

​Period comparison

​Finding trend chart

​Top finding categories

​Author performance tab

​Author table columns

​Developer profile dialog

​Filters

​Related

Leaderboard

Skill Matrix

Convention rules

Analytics tabs

Overview tab

Summary cards

Period comparison

Finding trend chart

Top finding categories

Author performance tab

Author table columns

Developer profile dialog

Filters

Related