dd-trace-py

Register a new environment variable / configuration option in dd-trace-py. Use whenever you add (or rename) a DD_*/_DD_*/OTEL_*/DATADOG_* environment variable so it is documented, validated, and tracked for cross-language feature parity. Covers supported-configurations.json, the generated _supported_configurations.py module, docs/configuration.rst, and the feature-parity registry hand-off.

Register a new environment variable / configuration option in dd-trace-py. Use whenever you add (or rename) a DD_*/_DD_*/OTEL_*/DATADOG_* environment variable so it is documented, validated, and tracked for cross-language feature parity. Covers supported-configurations.json, the generated _supported_configurations.py module, docs/configuration.rst, and the feature-parity registry hand-off.

Native crash log analysis for dd-trace-py

Native crash log analysis for dd-trace-py

dd-trace-py integration development guide. Use when creating, modifying, or debugging contrib integrations in the Python tracer. Covers the patch module system, context_with_data, context_with_event (new), registration, testing through the repository test runner, and common anti-patterns. LLM/AI integrations should use this skill for APM-side workflow only; use llmobs-integrations for LLMObs-specific lifecycle, extraction, streaming, and VCR guidance. Pin is DEPRECATED. Triggers: "dd-trace-py", "ddtrace", "contrib", "integration", "patch.py", "trace_handlers", "PATCH_MODULES", "context_with_data", "context_with_event", "TracingEvent", "VCR", "cassette", "generative-ai", "LLM integration", "run-tests", "suitespec", "new integration", "wrap", "unwrap", "manifest.yaml", "integration manifest".

Create or modify contrib instrumentation, integration registration, manifests, and APM integration tests.

Run circular import detection against ddtrace and propose architectural fixes for any cycles found. Use this when adding or refactoring modules, or when the detect_circular_imports CI job reports new cycles on a PR.

Run circular import detection against ddtrace and propose architectural fixes for any cycles found. Use this when adding or refactoring modules, or when the detect_circular_imports CI job reports new cycles on a PR.

Compare CPython source code between two Python versions to identify changes in headers and structs. Use this when adding support for a new Python version to understand what changed between versions.

Compare CPython source code between two Python versions to identify changes in headers and structs. Use this when adding support for a new Python version to understand what changed between versions.

Diagnose and fix slow base venv build times caused by unnecessary recompilation of native extensions (CMake, Cython, Rust) across test environment builds. Use when CI base venv builds are slow, when ext_cache isn't saving time, or when investigating warm build regressions.

Diagnose and fix slow base venv build times caused by unnecessary recompilation of native extensions (CMake, Cython, Rust) across test environment builds. Use when CI base venv builds are slow, when ext_cache isn't saving time, or when investigating warm build regressions.

Run the dependency direction detector against ddtrace and propose architectural fixes for any violations found. Use this when adding or refactoring modules under ddtrace/internal, ddtrace/contrib, or any product package, or when the detect_layering_violations CI job reports new violations on a PR.

Run the dependency direction detector against ddtrace and propose architectural fixes for any violations found. Use this when adding or refactoring modules under ddtrace/internal, ddtrace/contrib, or any product package, or when the detect_layering_violations CI job reports new violations on a PR.

Find all CPython internal headers and structs used in the codebase, particularly for profiling functionality. Use this when adding support for a new Python version to identify what CPython internals we depend on.

Find all CPython internal headers and structs used in the codebase, particularly for profiling functionality. Use this when adding support for a new Python version to identify what CPython internals we depend on.

Run targeted linting, formatting, and code quality checks on modified files. Use this to validate code style, type safety, security, and other quality metrics before committing. Supports running all checks or targeting specific checks on specific files for efficient validation.

Run targeted linting, formatting, and code quality checks on modified files. Use this to validate code style, type safety, security, and other quality metrics before committing. Supports running all checks or targeting specific checks on specific files for efficient validation.

dd-trace-py LLMObs integration development guide. Use when creating, modifying, or debugging LLMObs integrations for LLM/AI libraries in the Python tracer. Covers BaseLLMIntegration, stream handling, message extraction, usage metrics, tool call parsing, and VCR-based testing patterns. Triggers: "llmobs", "LLMObs", "BaseLLMIntegration", "llmobs_set_tags", "_llmobs_set_tags", "BaseStreamHandler", "submit_to_llmobs", "integration.trace", "LLM span", "VCR", "cassette", "anthropic", "openai", "google_genai", "claude_agent_sdk", "generative-ai", "LLM integration", "llmobs_enabled".

Create or modify LLMObs integration lifecycle, extraction, streaming, usage metrics, and tests.