>- Update/bump the libdatadog native library version in dd-trace-dotnet. Use when the user asks to bump, update, or upgrade libdatadog, or mentions a new libdatadog release version.
npx skills add https://github.com/DataDog/dd-trace-dotnet --skill bump-libdatadog
The native library is consumed as prebuilt binaries from GitHub releases of
DataDog/libdatadog-dotnet — the .NET-specific
distribution of libdatadog (a minimal feature preset: profiling, crashtracker, symbolizer,
library-config). This is not upstream DataDog/libdatadog.
> Version scheme: the pinned version is libdatadog-dotnet's own release version (e.g. v1.3.5),
> which is distinct from the upstream libdatadog version it is built from (tracked by LIBDATADOG_VERSION
> in that repo — e.g. libdatadog-dotnet v1.3.5 is built from upstream libdatadog v32.0.0). Pin the
> libdatadog-dotnet version here, not the upstream one.
There are two version pins to update, both from the same libdatadog-dotnet release:
| Platform | File | Hash type | Version format |
|----------|------|-----------|----------------|
| Linux/macOS | build/cmake/FindLibdatadog.cmake | SHA-256 | v<MAJOR>.<MINOR>.<PATCH> |
| Windows | build/vcpkg_local_ports/libdatadog/vcpkg.json + portfile.cmake | SHA-512 | <MAJOR>.<MINOR>.<PATCH> (no v prefix) |
A libdatadog-dotnet release builds all 8 platform artifacts together, so the two pins should normally
move to the same version in lockstep. Confirm with the user if they intend otherwise.
build/cmake/FindLibdatadog.cmakeUpdate these values:
LIBDATADOG_VERSION — the version tag (e.g. "v32.0.0")SHA256_LIBDATADOG_ARM64 — macOS arm64 hashSHA256_LIBDATADOG_X86_64 — macOS x86_64 hashSHA256_LIBDATADOG (aarch64 gnu) — Linux aarch64 glibc hashSHA256_LIBDATADOG (aarch64 musl) — Linux aarch64 Alpine hashSHA256_LIBDATADOG (x86_64 musl) — Linux x86_64 Alpine hashSHA256_LIBDATADOG (x86_64 gnu) — Linux x86_64 glibc hashArtifact filenames (from GitHub releases):
libdatadog-aarch64-apple-darwin.tar.gzlibdatadog-x86_64-apple-darwin.tar.gzlibdatadog-aarch64-unknown-linux-gnu.tar.gzlibdatadog-aarch64-alpine-linux-musl.tar.gzlibdatadog-x86_64-alpine-linux-musl.tar.gz (note: uses ${CMAKE_SYSTEM_PROCESSOR} in filename)libdatadog-x86_64-unknown-linux-gnu.tar.gz (note: uses ${CMAKE_SYSTEM_PROCESSOR} in filename)build/vcpkg_local_ports/libdatadog/Two files:
vcpkg.json — update "version-string" (no v prefix)portfile.cmake — update SHA-512 hashes for x64 and x86 Windows zipsArtifact filenames:
libdatadog-x64-windows.ziplibdatadog-x86-windows.zipAsk the user for the target version, or check the latest release:
https://github.com/DataDog/libdatadog-dotnet/releases
SHA-256 and SHA-512 checksums are published directly in the GitHub release notes. Either:
https://github.com/DataDog/libdatadog-dotnet/releases/tag/v<VERSION> and copy from the checksums sections, orbash .claude/skills/bump-libdatadog/scripts/fetch-release-hashes.sh <VERSION>
Where <VERSION> is without the v prefix (e.g. 1.3.5).
The release notes contain:
FindLibdatadog.cmake (6 Linux/macOS artifacts)portfile.cmake (2 Windows artifacts)build/cmake/FindLibdatadog.cmakeLIBDATADOG_VERSION to "v<VERSION>"SHA256_LIBDATADOG* value with the new SHA-256 hash from the script outputbuild/vcpkg_local_ports/libdatadog/vcpkg.jsonUpdate "version-string" to the new version (no v prefix).
build/vcpkg_local_ports/libdatadog/portfile.cmakeReplace the SHA-512 hashes for x64 and x86 Windows builds.
# Linux — validates CMake SHA-256 hashes during configure
./tracer/build.sh CompileProfilerNativeSrc
# Windows — validates vcpkg SHA-512 hashes during install
.\tracer\build.cmd CompileProfilerNativeSrc
These don't contain version strings but may need refreshing after a bump if the exported symbol set or glibc requirements change:
tracer/build/_build/NativeValidation/native-libdatadog-symbols-alpine-x64.verified.txttracer/build/_build/NativeValidation/native-libdatadog-symbols-alpine-arm64.verified.txtCI will fail if the symbol list changes — re-run the Alpine symbol validation step and accept the new snapshot.
Because libdatadog-dotnet ships a reduced feature set (no data-pipeline, log, telemetry,
ddsketch, or ffe), its exported symbols are a strict subset of upstream libdatadog — so these
snapshots reflect that smaller set. The glibc cap in Build.Profiler.Steps.cs
(libdatadog_profiling ≤ 2.15 on x64, ≤ 2.17 on arm64) still applies and is unchanged by the source
switch — libdatadog-dotnet x64 builds are capped at GLIBC 2.15, same as upstream.
Several files under tracer/src/Datadog.Trace/LibDatadog/ have XML doc comments linking to a specific upstream libdatadog git SHA (e.g. 60583218a8de6768f67d04fcd5bc6443f67f516b). These are informational only and can be updated for traceability (use the upstream SHA the libdatadog-dotnet release was built from):
VecU8.cs, CharSlice.cs, Error.csServiceDiscovery/ResultTag.cs, ServiceDiscovery/TracerMemfdHandleResult.csprofiler/Directory.Build.targets — Windows link dependencies for libdatadogtracer/build/_build/Build.Steps.cs — copies libdatadog binary to monitoring hometracer/build/_build/Build.Profiler.Steps.cs — profiler build steps; glibc version expectations for Alpine.gitlab/one-pipeline.locked.yml — CI pipeline (auto-generated, don't edit manually)vcpkg.json (root) — declares dependency on libdatadog (no version pin here)vcpkg-configuration.json — overlay ports config## Checksums).v prefix (v1.3.5); vcpkg does not (1.3.5).Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
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React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take datadog/bump-libdatadog from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.