Looking to migrate from Trunk? Compare Trunk vs TestDino. TestDino groups errors, embeds traces, feeds AI coding agents, and bills flat.
Trunk is a flaky test detection platform. It batches PRs, isolates unstable tests, and surfaces failure rates over time. TestDino ships similar capabilities for Playwright teams, plus the parts Trunk leaves out. TestDino is a Playwright-focused test intelligence platform. It groups errors by root cause, ships an embedded Playwright trace viewer on every failure, and ties each run to its pull request with a dedicated Pull Request view.
TestDino also comes with built-in test management designed for how engineering works in 2026. Test cases live alongside their run history, manual runs, and exploratory sessions roll up under date-bound releases, and the entire test record is queryable by Claude Code, Cursor, or any MCP-compatible agent, so your AI coding tools aren't debugging blind.
Trunk vs TestDino is a question of detection vs. classification. Here's where TestDino adds the layers Trunk doesn't ship.
Ease of setup
One npm package, one environment variable, and your first Playwright run lands a full dashboard. No separate uploader CLI. The reporter handles it end-to-end.
Full failure context in one view
Every failed test opens with an embedded trace viewer showing screenshots, video playback, and error groups by message, stack trace, and location. Debugging happens in the test reporter.
MCP-native test access
The TestDino MCP Server lets Cursor and Claude Code work directly with your Playwright test history. Agents debug failures with full trace context, rank flaky tests, and update manual cases through create_manual_test_case straight from the editor.
Flat pricing that doesn't scale per committer
$39/month billed annually for up to 3 users with 10,000 executions included. The free tier includes 5,000 executions and every core feature.
Limited failure context
There's no Playwright trace viewer or video playback. Teams find debugging harder because the actual browser state at the moment of failure lives in CI artifacts they have to track down separately.
Detection-focused, not classification-focused
AI in Trunk groups similar failures and detects flake patterns, but it doesn't tell you whether a failure is a real bug, a UI change, or noise. Developers still read stack traces manually.
No Playwright-native features
It doesn't surface Playwright projects, fixtures, test annotations, or visual regression data as first-class concepts.
Per-committer pricing that scales with your team
The Team plan counts every committer to private repos in the last 30 days. Costs can grow quickly as engineering teams scale, and enterprise features like SSO require custom pricing.
| | |
|---|---|---|
| Pricing (starts at) | $39/month (billed annually) | Free up to 5 committers, then custom |
| Best for | Playwright test intelligence & management | AI-driven flaky detection + auto-quarantine |
| Playwright integration | Native (trace viewer, error grouping, MCP) | Native via uploader |
| Ease of use |  |  |
| One-step CI setup | Single CLI uploader + token | |
Dashboards & Reporting | ||
| Unified Playwright dashboard | ||
| Multi-tab test run detail view | Summary, History, AI Insights & more | |
| Pull request insights (per-PR history) | ||
| Test ExplorerBrowse tests as a hierarchy, a flat list, or by tag. | By file/owner; tag filter limited | |
| Real-time streaming | Per-shard/worker | |
| Scheduled PDF reports (email) | Daily/Weekly/Monthly | |
Test Analytics | ||
| Analytics: trends & patterns | ||
| Code coverage, per-file | Istanbul, run-level | |
| Environment analytics | Pass-rate/flaky by env | Environment segmentation |
Debugging & Evidence | ||
| Built-in Playwright trace viewer | ||
| Screenshots & video replay | Embedded | |
| Console logs (per test) | Node + browser | Stack traces + CI logs only |
| Visual diff comparison | ||
| Smart error grouping | Message/stack/location | |
| Flaky detection (+ stability %) | ||
| Playwright tags & annotations | Priority/owner/links/metrics | Owner/team via CODEOWNERS |
CI/CD Optimization | ||
| GitHub CI Checks quality gates | Per-env + mandatory tags | |
| Branch → environment mappingMatch each Git branch to the environment it runs against. | Exact/regex | |
| Sharded / parallel run support | Per-shard live view | |
| Native CI breadth | GitHub, GitLab, Azure DevOps, TeamCity, Bitbucket, CircleCI, Jenkins | GitHub Actions, GitLab, CircleCI, Buildkite, Jenkins, Semaphore, Harness |
| Self-managed GitLab | ||
Test Management | ||
| Test case management (suites, ownership) | CODEOWNERS, no case authoring | |
| Bulk test creation (PRDs/Jira/stories) | via MCP | |
| Release tracking (releases/cycles/sprints) | ||
| Exploratory / manual sessions | ||
| Import / export test cases | JSON/CSV/ZIP | |
AI & Automation | ||
| Local MCP (IDE agents) | Cursor/Claude Code/Copilot | Remote-hosted MCP only |
| Remote MCP (web AI) | ||
| AI test run summary on GitHub PRs | PR summaries for flaky tests | |
| AI test suite audit (audit score + report) | Flake-rate scoring | |
| AI failure classification | ||
Integrations & Collaboration | ||
| Bug tracking breadth | Jira, Linear, Asana, monday | Jira, Linear, webhooks |
| Slack notifications (run summaries) | App + webhooks | Native Slack alerts |
Platform & Security | ||
| Public API & CLIs | REST + @testdino/playwright | REST API + Trunk CLI |
| Project-level AI controls | Per-feature toggles | OAuth-scoped, repo-level |
| Compliance & certifications | ISO 27001, SOC 2 Type II, GDPR | SOC 2 Type I + Type II |
Plans & Pricing | ||
| Plan tiers | Free · Pro $39 · Team $79 · Enterprise | Free · Team (free, unlimited committers) · Enterprise |
| Free executions | 5,000/mo | 1M test spans/committer/mo |
| Support | Chat + Slack Connect + Priority email | Community (Free) · Onboarding (Team) · Dedicated (Ent) |
| Start for Free | ||
Feature-by-feature breakdown showing how each tool handles the areas that matter most to testing teams.
The Trunk dashboard focuses on flaky and broken test metrics. There's no detailed test run view, dedicated PR & Specs view, scheduled PDF reports, or real-time streaming.
AI groups similar failures by stack trace embeddings. But there's no trace viewer, screenshots, video, DOM snapshots, or network panel, so the actual browser state during a Playwright failure isn't available inside Trunk.
AI focuses on flake detection and grouping. What's missing is classification, so every failure still needs a developer to categorize whether it's a real bug, a UI change, or noise.
list_testruns, debug failures with full trace and artifact context through debug_testcase, and rank flaky tests across recent runs through list_testcase.Trunk's MCP integration is built for AI-powered flake fixing, currently in beta.
Trunk's CI optimization focuses on quarantining flakes to prevent them from blocking PRs. Environment mapping via branch regex and per-environment trend analysis aren't part of Flaky Tests as a standalone feature set.
There's no test case management, no nested suites, no manual tests, and no TestRail or CSV import. Ticketing integrations cover Jira, Linear, and GitHub Issues through webhooks, but Asana and monday aren't supported.
Purpose-built capabilities that help Playwright teams ship faster and debug smarter.
Where each platform leads, and where it falls short.
Trunk is a flaky test detection and quarantine platform that keeps CI green and integrates with merge queues and ticketing systems.
Stack Trace Embeddings
Failure modes fingerprinted by embeddings rather than error-string matching.
Branch-Aware Flake Detection
Main, PR, and merge queue failures are analyzed with different rules, so expected failures during PR development don't trigger false positives.
Bundled Platform
Flaky Tests, Merge Queue, and Code Quality are included in the same subscription.
TestDino is a Playwright-native AI test intelligence platform that brings debugging evidence, AI classification, and test case management into one reporter.
Debugging Without Leaving the Reporter
Trace viewer, screenshots, video, and console logs all open inline on the failed test. No artifact downloads, no CI tab switching, no trace zip file hunting.
TestDino MCP Server
Lets AI coding agents query Playwright test runs, debug failures with full retry and artifact context, detect flaky tests, and manage manual test cases and suites, all from the editor.
Playwright-Native Workflow
Projects, fixtures, visual regression, and trace viewer are all first-class features. The reporter matches the way Playwright actually works.
Test Case Management Built In
Nested suites, TestRail import, bulk ops, and bug filing pre-filled for Jira, Linear, Asana, and monday. Not bolted on with a separate tool.
Verified reviews from QA and engineering teams running Playwright in production.
Analyzing failed Playwright runs in CI used to eat up a lot of our time. TestDino solved that with a centralized dashboard that pulls in screenshots, logs, and failure trends in one place. What's been most useful is the automatic grouping of failures, since instead of checking each failing test individually, we can immediately see patterns and likely causes. It's made triaging failures, and identifying which tests are simply flaky, dramatically faster.
Lead Software Engineer
We inherited an existing test suite without much context on how it was built, and TestDino gave us a real way to take ownership of it. It shows us clearly which tests are the slowest, the flakiest, and the ones failing most often, which has been essential for knowing where to focus our effort. It's given us the visibility to understand the current state of the code and steadily improve its reliability.
Senior QA Engineer at Penpot by Kaleidos
I monitor everything my tests do, from the full list of tests to detailed error screenshots. The GitHub integration is smooth, so commit hashes, CI runs, and HTML reports open straight from the dashboard. I use TestDino almost every day, and it has improved the quality of our automation code.
Lead QA Automation Engineer
Before TestDino, we were manually digging through raw reports to catch flaky and failing tests, and it took a lot of time. Now everything is stored and analyzed automatically, with no extra setup layers needed. The installation itself was simple, and it's made spotting flaky tests a much faster, cleaner process for our team.
Test Automation Team Lead
TestDino gives us a clean dashboard and reporting setup that's genuinely easy to work with, packed with useful analytics. It's effectively replaced what used to be a custom Power BI dashboard for us, while being far simpler to set up and maintain. The platform makes it easy to centralize and visualize results, so tracking trends and understanding failures no longer takes extra effort.
QA Automation Engineer
Reviewing our Playwright test results used to mean sifting through raw output to figure out what actually broke. TestDino changed that by giving us a clear, structured view of every run. Failed tests are easy to spot right away, and debugging that used to take real effort now moves a lot faster.
Automation Engineer
Enterprise-grade security so your team can focus on shipping instead of worrying about data.
Secure authentication, role-based access control, and data encryption safeguard your test data in transit and at rest.
Persistent analytics with historical tracking deliver reliable insights about test performance, coverage, and release readiness.
Automated backups and retention policies maintain a complete history of test data. Project-scoped access prevents unauthorized changes.
Trunk uses per-committer pricing with test span caps. TestDino offers flat monthly pricing with predictable costs for Playwright-focused teams.
For teams that need flaky test detection and merge queue management
Unlimited committers on Team
1M test spans per committer per month
Flaky Tests, Merge Queue, Code Quality bundled
Jira, Linear, GitHub Issues ticketing
Google/Microsoft/GitHub SSO
Email support
For dev teams shipping to production. Flat pricing, no per-committer overage.
10,000 test executions per month
Up to 3 users
60-day data retention
AI failure classification
TestDino MCP Server with test case writes
PR view and CI/CD optimization
Embedded trace viewer and debugging features
Integrations with Jira, Linear, Asana, Slack
Stop wasting time on
flaky tests
Yes. TestDino catches flakes the moment a test passes on retry inside the same run, then layers cross-run pattern detection on top so the team has an actionable signal from day one rather than after a long historical baseline.
Side-by-side comparisons of features, pricing, and integrations to help you pick the right testing tool.
