QA tools for coding agents: what each one checks

Choose the check you are missing

If your agent can run a terminal command, it can already use a test runner. Add another QA tool when those tests and reports leave a question unanswered.

This guide is written by the Supercov team. We ran the small code-coverage examples linked below. The browser, reporting and test-management comparisons are based on their maintainers’ documentation, not a hands-on ranking of which product finds the most bugs. Sources were checked on September 14, 2026.

Native coverage: start here

For a Vitest project with its coverage provider installed:

npx vitest run --coverage

An agent can read this output. Vitest even adapts its default text coverage report in agent environments, omitting fully covered files and adding a totals summary. There is no need to replace it just to obtain agent-readable output. See Vitest’s coverage documentation.

For Python, pytest-cov can record individual test contexts with --cov-context=test; attributing executed code to tests is not exclusive to Supercov. See the Python comparison.

A covered branch can still hide an untested condition or an unchecked return value. The Vitest example demonstrates both.

Supercov: conditions and assertion coverage

Supercov is a tool your coding agent runs, not another agent. It measures the existing suite and exposes details the agent can query:

npx supercov -- npm test
npx supercov runs latest
npx supercov runs latest gaps

MC/DC identifies conditions without evidence of independently changing a decision. That can expose a missing session-expiry test even when both the allowed and denied branches already run. The MC/DC guide includes the original tests, actual output and the missing case in five languages.

Assertion coverage requires another step: the agent reviews recorded source and assertions, writes a map, and has Supercov validate it against runtime evidence. An ordinary test run does not produce a completed assertion assessment. The assertion guide explains that workflow.

This does not verify requirements, replace browser testing, or prove that a mapped assertion detects every possible bug.

Stryker: would a code change make a test fail?

Stryker changes operators, expressions and other parts of your code, then runs tests against those mutations. Surviving changes give the agent specific examples of behavior the suite may fail to distinguish.

For a project with Stryker and its runner integration configured:

npx stryker run

The setup guide covers installation and configuration. Start with an important module if running mutations across the whole repository is too expensive.

This is a stronger check of sensitivity to the chosen mutations than a line-coverage percentage. Some survivors do not change observable behavior; some real bugs are not generated by the operators. Inspect the survivors, not just the score.

Playwright: test the running app

An agent can edit and run an existing Playwright suite through the terminal. Interactive browser access is useful when it needs to inspect the app before saving a regression test. Playwright also supplies planner, generator and healer workflows for coding agents. See Playwright Test Agents.

Those workflows need a usable test environment, including the starting state and any authentication. They cannot infer every business requirement from the page. Review generated assertions and repairs: Playwright documents that the healer may skip a test when it believes the feature is broken. A skipped test is not a fixed bug.

Shiplight: browser workflows inside the coding agent

Shiplight combines browser MCP tools with skills for verification and regression-test creation. Its tests are stored as YAML in the repository; hosted features add scheduled runs and shared results. Its documentation says local browser automation and authoring do not require a Shiplight account. See its coding-agent workflow and local and hosted setup.

Try a real regression and a harmless UI change. Check what it repairs, what it reports as a bug, and which artifacts you can rerun in CI.

Check where browser data and results are processed in the mode you choose. A local command does not necessarily mean all data stays local.

Allure: make test results easier to investigate

Allure Agent Mode gives agents a reporting view of existing runs: what ran, what failed, what was skipped or retried, and the steps, logs and attachments recorded by the test framework.

Once Allure reporting is configured:

allure agent -- npm test

This requires Allure Report 3.12 or newer and a framework adapter that emits Allure results. It is not a zero-setup wrapper for arbitrary terminal output. See the Agent Mode requirements.

Use it when the agent lacks context to diagnose a failure, particularly when that evidence already exists in CI artifacts.

Qase: give agents the same test context

Qase MCP connects agents to a project’s cases, suites, runs, results and defects. Agents can read that context and make updates within project permissions. Expected behavior and testing history may live outside the repository.

See Qase’s test-management workflow for coding agents. Start with restricted access and review writes before allowing bulk changes.

A saved test case still needs execution. Adding it to Qase does not demonstrate that the application passes it.

Try one tool against one known problem

Keep your runner and choose an additional check that matches the problem:

• An important condition is never tested independently: inspect MC/DC gaps.
• A calculation is covered but can be wrong without failing tests: try mutation testing and review exact assertions.
• A feature fails only in the UI: save and rerun a browser regression test.
• CI fails and the agent cannot explain why: preserve test-level logs and artifacts.
• The agent does not know the agreed behavior: provide requirements and the existing test cases.

Give every candidate the same task and time allowance. Keep a known regression outside the agent’s workspace, then check whether the saved tests detect it. Record setup failures and unfinished runs as well as successes. A small experiment in your project is more useful than an overall ranking.

In our nine-session checkout comparison, native coverage, Supercov and Stryker workflows all caught the same 16 selected faults. That small fixture did not establish an advantage for the extra tools.

For a starting workflow, see testing with Claude Code or working with your agent.