Back to directory

Axolotl

An AI QA agent for VS Code that reads a pull request's diff, generates a test plan, opens a real browser to click through the app, and reports whether the change is safe to merge.

Axolotl

Axolotl analyzes a pull request's code changes, figures out what should be tested, and then actually tests it in a real browser against the running application, instead of relying only on eyeballing a diff and an existing test suite. A QA session can start from a PR number, uncommitted changes, specific files, or a chat prompt.

Its pipeline uses tree-sitter AST parsing and ripgrep pattern search to understand the code structure before writing tests, searches the web for testing practices specific to the project's tech stack to generate targeted test cases, and can run the project's own lint, typecheck, and test scripts on the changed files first, forwarding any real CI failures as context into the test planner so the generated plan is not built around hallucinated bugs. After a reviewer approves the generated test plan, Axolotl injects temporary log markers, runs real browser-based end-to-end tests while monitoring both frontend UI and backend output, and produces an evidence-backed pass/fail verdict per test case. It requires an Anthropic API key, and web search during test-case generation uses a separate search API key.

More in Testing

See all 69
  • Canary

    runcanary.ai

    An independent testing service, backed by Y Combinator, that runs an application and tries to break every change an AI coding agent makes, reporting what would have reached production.

  • MoEWatch

    github.com

    A diagnostic and audit library for Mixture-of-Experts models in HuggingFace Transformers that instruments router modules to catch expert collapse, routing entropy collapse and load imbalance during training.

  • Mockwave

    github.com

    An open-source, multi-protocol mock server for HTTP, GraphQL, SOAP, and gRPC, with weighted traffic splitting, dynamic JavaScript responses, chaos-testing fault injection, and an MCP server so an AI assistant can generate mock rules directly.