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rules_test_optimization
rules_test_optimization contains 4 collected skills from DataDog, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Use when instrumenting a Bazel Go repository or monorepo with Datadog Test Optimization and Orchestrion. Applies to WORKSPACE and Bzlmod consumers, large monorepos with local Go wrappers, doctor/uploader validation, and RFC-safe setup that avoids patches, payload proxies, DD_GIT_* test environment variables, and missing remote outputs.
Use when instrumenting a Bazel Java repository or monorepo with Datadog Test Optimization. Applies to Bzlmod and WORKSPACE consumers, direct java_test targets, repository-owned Java/JUnit wrapper macros, doctor/uploader validation, and RFC-safe setup that avoids manual tracer payload wiring, DD_GIT_* test environment variables, uploader credentials in test sandboxes, and missing remote outputs.
Use when instrumenting a Bazel Python repository or monorepo with Datadog Test Optimization. Applies to Bzlmod and WORKSPACE consumers, managed pytest targets, repository-owned pytest wrappers, consumer_runner mode, doctor/uploader validation, and RFC-safe setup that avoids payload proxies, DD_GIT_* test environment variables, and missing remote outputs.
Use when porting this repository's vendored Orchestrion-enabled rules_go fork from its current upstream base to another upstream rules_go tag or commit. Applies to base support lines, metadata regeneration, profile verification, smoke validation, and migration PR preparation.