“API testing”

Test system for Megatron-LM.

Unified testing commands and patterns across frontend and backend.

Design controlled social copy experiments and publish or schedule test variants through BulkPublish with measurable hypotheses.

Skill validation framework PLUS daily test-suite health and regression intelligence.

Use when designing or reviewing API contracts, versioning decisions, and governance standards.

Use when writing or fixing Jest tests, mocks, or test layout under test/ in contentstack-js-core.

Tests Amazon MWAA workflow execution end-to-end: trigger a run and monitor it to completion for Provisioned (Python DAG, via Airflow REST API) and Serverless…

Use when testing local API endpoints with auto-generated data.

測試驗證階段，負責雙軌測試執行（pytest API 測試 + Playwright UI 測試）、Bug 追蹤與分類、測試覆蓋率報告產出，以及回歸測試策略制定。

Use for JUnit tests, integration (*IT) tests, fixtures, and credentials handling in contentstack-java.

Use for XCTest targets, DVR, and CI config secrets in contentstack-swift.

Use for Jest e2e and TypeScript test suites, jest configs, and test layout in contentstack-javascript.

Ginkgo/Gomega testing patterns for Konflux — test cleanup (envtest), Eventually/Consistently soft assertions, and helper conventions.

Design Ash regression tests or remove redundant test coupling.

Add, update, or diagnose pytest coverage for RLM behavior using focused fake environments and optional Docker integration tests.

Implement A/B testing with feature flags, experiment frameworks, and statistical analysis

Use when writing or reviewing tests in any stack — unit tables, API cases, or browser end-to-end flows.

Write deterministic tests that fail for real product defects.

Use when verifying an incident fix and reporting its results.

Write, extend, or evaluate automated tests — unit, integration, or end-to-end — in a way that matches the project's existing framework and conventions.

Red-green-refactor as the default for real feature and bug-fix work; use verification-first when behavior is already clear.

Staged pipeline for AI-assisted test generation: requirements extraction → risk analysis → coverage matrix → scenario generation → oracle design → test code →…

Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers and stand the test of time.

Test abstractions, not hardware — discovery, capabilities, NAT/firewall generation, cleanup, rollback, uplink switching.