Ask five people on your team "how's our code quality?" and you'll get five different answers. cheer.dev gives everyone the same number — driven by policy, tracked over time, drillable on demand.
Not because it doesn't exist — but because there's no common language for it. Security teams measure CVEs. Developers track test coverage. Engineering managers look at velocity. QA counts bugs. Nobody's speaking the same language, and nobody has the full picture.
So when leadership asks "are we ready to ship?" the answer is a conference call, three dashboards, and a qualified "probably."
SonarQube shows code smells. Snyk shows vulnerabilities. Your CI shows pass/fail. None of them roll up into a single view that means the same thing to your CTO, your tech lead, and your new hire. None of them score AI governance. None of them show how quality changes version to version.
You don't need more data. You need a score.
cheer.dev scores every component 0-10 across 5 categories: Hygiene, Quality, Security, Trust, and Velocity. Weighted by policies your team configures. Tracked per version. Trended over time. Drillable from workspace health → category → component → version → individual finding.
It's as easy to understand as a credit rating. And as configurable as your CI pipeline. When your CEO asks "how's our quality?" — you have an answer.
The Overview dashboard shows your workspace's Overall Health score — a weighted rollup of every component across all 5 categories. Trend arrows show whether you're improving or declining. The severity distribution chart shows how many findings are Critical, Major, Minor, or Info. The category breakdown shows where your strengths and gaps are.
This is the page you show in your weekly engineering standup. The page you screenshot for the board deck. The page that answers "how are we doing?" without a 30-minute explanation.
Workspace health tells you the big picture. Component detail tells you the story.
Each component gets its own dashboard: score trends across versions, activity timeline, version history with individual scores. Click into a version to see the specific findings — which rules passed, which failed, what changed since the last evaluation.
You can track how a component's quality evolves as your team iterates. See the impact of a refactor. Identify a regression before it ships. Understand whether that new hire's first PR improved or degraded the component's health.
A score of 5.3 is useful. Knowing why it's 5.3 is actionable.
Findings aggregate across your workspace — filterable by severity, category, and source (External Tools, AI Analysis, Policy Evaluation). Each finding shows what's wrong, which policy rule triggered it, the expected vs. actual value, and step-by-step remediation guidance.
The summary cards give you the macro: total open findings, breakdown by severity, breakdown by category, breakdown by source. The detail view gives you the micro: specific conditions, affected components, and exactly what to do next.
The Score Trend chart shows your workspace's quality trajectory over 7, 30, or 90 days. Are you improving after that security push? Did the new linting rules move the Hygiene score? Is Trust declining as AI adoption increases?
Trends answer the questions that point-in-time scores can't. They show whether your investments in quality are paying off. They give you the data to justify (or challenge) resource allocation. And they make quality a conversation about direction, not just current state.
Developer time lost to technical debt: 40%
— CodeScene, 2025
Increase in code duplication from AI tools: 800%
— GitClear, 2024
Quality problems compound when they're invisible. cheer.dev makes them visible — with a number everyone understands and findings everyone can act on.
5 categories, configurable policies, per-version evaluation. The intelligence layer that powers visibility.
Learn about Scorecard →ReleaseThe scores you see here drive the quality gates that govern your releases. From measurement to deployment.
Learn about Release →0-10 scoring across 5 categories. Tracked per component, per version, over time.