AI Skills for QA / Test Engineer

Guides agents in conducting thorough code reviews for local changes and remote Pull Requests, ensuring code quality and adherence to standards.

Enables fast web browsing for Claude Code with a headless Chromium daemon, allowing navigation, content extraction, and interaction with web pages.

Facilitates systematic debugging and root cause analysis for software issues, ensuring effective problem resolution.

Conducts thorough QA testing on web applications, generating detailed reports without fixing any issues.

Provides safety guardrails for destructive commands, warning users before executing potentially harmful operations in production environments.

Enables fast web browsing and interaction with web pages via a headless Chromium daemon for efficient data extraction and testing.

Systematically tests web applications to identify bugs and ensure quality, producing structured reports with evidence.

Imports cookies from real browsers into headless sessions for QA testing, enhancing authentication handling in automated tests.

Conducts live audits of developer experience, evaluating documentation and onboarding processes to produce actionable scorecards.

Facilitates systematic debugging and root cause analysis through a structured four-phase approach for effective issue resolution.

Facilitates engineering plan reviews by locking in execution strategies, addressing edge cases, and ensuring thorough documentation.

Analyzes commit history and work patterns to generate engineering retrospectives, enhancing team performance and code quality.

Analyzes pull requests for SQL safety and structural issues, ensuring code quality before merging.

Monitors post-deploy performance and errors, ensuring application stability with alerts on anomalies and visual comparisons.

Provides a CLI wrapper for OpenAI Codex with modes for code review, challenge, and consultation, enhancing coding efficiency.

Provides a comprehensive code quality dashboard that evaluates and tracks the health of codebases over time.

Automates the codification of successful scrape flows into permanent browser skills, enhancing efficiency and speed.

Guides developers on effectively receiving and verifying code review feedback to ensure technical correctness and clarity.

Provides a systematic approach to debugging technical issues by emphasizing root cause investigation before proposing fixes.

Ensures work claims are backed by verification evidence, promoting honesty and accuracy before committing code or creating PRs.