LLM Torch Profiler Analysis
sgl-project/sglang
Unified LLM torch-profiler triage skill for sglang, vllm, TensorRT-LLM, and TokenSpeed.
A skill your agent uses when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVPDigest) onto DOCA SHA…
$ npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills doca-sha-offload-engine --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/doca-sha-offload-engine .claude/skills/doca-sha-offload-engine && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "doca-sha-offload-engine" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sha-offload-engine into .claude/skills/doca-sha-offload-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sha-offload-engine", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA/skills/tree/main/skills/doca-sha-offload-engineType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills doca-sha-offload-engine --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/doca-sha-offload-engine .agents/skills/doca-sha-offload-engine && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "doca-sha-offload-engine" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sha-offload-engine into .agents/skills/doca-sha-offload-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sha-offload-engine", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills doca-sha-offload-engine --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/doca-sha-offload-engine .cursor/skills/doca-sha-offload-engine && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "doca-sha-offload-engine" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sha-offload-engine into .cursor/skills/doca-sha-offload-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sha-offload-engine", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA/skills.git --path skills/doca-sha-offload-engine--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills doca-sha-offload-engine --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/doca-sha-offload-engine .gemini/skills/doca-sha-offload-engine && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "doca-sha-offload-engine" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sha-offload-engine into .gemini/skills/doca-sha-offload-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sha-offload-engine", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA/skills doca-sha-offload-engineInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/doca-sha-offload-engine .github/skills/doca-sha-offload-engine && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "doca-sha-offload-engine" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sha-offload-engine into .github/skills/doca-sha-offload-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sha-offload-engine", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA/skills doca-sha-offload-engine --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/doca-sha-offload-engine .opencode/skills/doca-sha-offload-engine && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "doca-sha-offload-engine" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sha-offload-engine into .opencode/skills/doca-sha-offload-engine/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sha-offload-engine", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
doca-sha-offload-engineA skill your agent uses when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVPDigest) onto DOCA SHA…
Doca Sha Offload Engine is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Use this skill when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVPDigest) onto DOCA SHA hardware without rewriting against doca-sha. Covers engine load mechanics (openssl engine dynamic, setpciaddr ctrl, -engineimpl), the SHA-224 negative test that proves offload engaged, the message-size window where offload beats CPU SHA, and engine-vs-library selection. Trigger even when the user does not say "DOCA SHA Offload Engine"…
Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files (for example `BENCHMARK.md`, `CAPABILITIES.md` and `SKILLCARD.yaml`). Compatibility notes: Requires DOCA SDK installed at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField DPU or ConnectX NIC attached, plus OpenSSL ≥…
It works with NVIDIA AI Platform. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 0e0d506. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
opensslFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Requires DOCA SDK installed at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField DPU or ConnectX NIC attached, plus OpenSSL ≥ 1.1.1 and libssl-dev (or distro equivalent) on the build host. The engine ships under /opt/mellanox/doca/tools/doca_sha_offload_engine/ as libdoca_sha_offload_engine.so; reads the user's local install via `pkg-config doca-sha` and inspects /opt/mellanox/doca/{lib,include,samples,applications}.
From compatibility in the SKILL.md frontmatter.
Doca Sha Offload Engine loads about 4k tokens when it runs. Until then it costs about 254 tokens; SKILL.md has 1,800 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from NVIDIA/skills at commit 0e0d506, republished under its Apache-2.0 licence (© NVIDIA). 1,800 words, ~3,954 tokens.
.claude/skills/doca-sha-offload-engine/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.Where to start: This is a tool skill for the OpenSSL
ENGINE shipped in the DOCA SOURCE tree under
doca/tools/sha_offload_engine/ and INSTALLED on the host
under ${DOCA_DIR}/tools/doca_sha_offload_engine/ as
libdoca_sha_offload_engine.so. The directory-name shift
(sha_offload_engine in the source layout vs
doca_sha_offload_engine in the install layout) is an
NVIDIA packaging convention, not a bundle inconsistency;
both forms appear below and are the same artifact at
different lifecycle stages — quote whichever the prompt is
about (build-from-source vs runtime-load). It is not a CLI —
it is a shared object loaded by an OpenSSL-based
application or by openssl itself, that re-routes SHA-1 /
SHA-256 / SHA-512 (one-shot only, via the EVP_Digest
interface) onto the DOCA SHA hardware path. Open
TASKS.md and start at
## configure for the PCIe-address
configuration and the OpenSSL prerequisites; jump to
## run for the "load the engine and
prove it actually runs" flow. Open
CAPABILITIES.md when the question is
what the engine actually offloads vs falls back to,
when the engine is a perf win vs not, or how to verify
offload actually engaged. If DOCA is not installed yet,
route to doca-setup first.
If the user is building a new SHA pipeline from scratch
(not wrapping an existing OpenSSL-based one), this skill
is the wrong surface — route to
../../libs/doca-sha/SKILL.md
instead.
The CLASSES of doca-sha-offload-engine questions this
skill is built to answer, each with one worked example.
The class is the load-bearing piece; the worked example
is one instance.
EVP_DigestInit_ex / EVP_DigestUpdate /
EVP_DigestFinal_ex against EVP_sha256(); can I
drop in DOCA-SHA offload via an engine load?".
Answered by the "when this engine is the right
surface" rule in
CAPABILITIES.md ## Capabilities and modesTASKS.md ## configure.openssl dgst invocation completed; how do I know
DOCA SHA actually did the work and OpenSSL did not
silently use the software path?". Answered by the
"prove the engine actually ran" pattern in
CAPABILITIES.md ## Observability
(the SHA-224 negative test and the -engine_impl
flag) + the verification flow in
TASKS.md ## test.CAPABILITIES.md ## Capabilities and modesopenssl speed perf-comparison pattern in
TASKS.md ## test.CAPABILITIES.md ## Capabilities and modes.CAPABILITIES.md ## Capabilities and modes.CAPABILITIES.md ## Version compatibility
(verified surface: the engine is documented for
OpenSSL 1.1.1f on Ubuntu 20.04 and OpenSSL 3.0.2 on
Ubuntu 22.04 per the shipped readme.md).This skill serves external developers and operators who have an existing OpenSSL-based pipeline doing SHA hashing and want to offload SHA onto DOCA SHA without rewriting their application against the doca-sha C API. Concretely:
EVP_Digest for SHA-1 /
SHA-256 / SHA-512.openssl dgst / openssl speed based pipeline and wanting to measure the win
from DOCA SHA offload without changing the pipeline's
invocation surface.It is not for users building a new SHA pipeline from
scratch (route to
../../libs/doca-sha/SKILL.md),
not for users wanting MD5 / SHA-2-224 / SHA-3 /
HMAC-SHA offload (the engine does not implement those —
the verified surface per the engine's source is one-shot
SHA-1, SHA-256, SHA-512 via EVP_Digest), and not a
substitute for the public DOCA SHA programming guide.
The DOCA SHA Offload Engine is shipped as a C dynamic
shared object (libdoca_sha_offload_engine.so) built
from doca/tools/sha_offload_engine/{engine/doca_sha_offload_engine.c, lib/doca_sha_offload_lib.{c,h}} via meson. Its
consumer interface is OpenSSL's ENGINE API; any
language that calls OpenSSL (C, C++, Rust via openssl
crate, Python via cryptography and pyca/cryptography's
backend, Node via node:crypto) can therefore use the
engine, provided the language binding either calls
ENGINE_load_dynamic / ENGINE_by_id directly or honors
an OpenSSL engines config that loads it. The skill's
language-neutral contribution is the engine-load mechanics
and the verification pattern; the OpenSSL ENGINE API is
the contract.
Load this skill when the user is — or the agent needs to — deploy the DOCA SHA Offload Engine into an OpenSSL-based pipeline on a host with DOCA installed and a SHA-capable device. Concretely:
openssl CLI invocation, with the
intent of no source-level code changes (or only the
minimum ENGINE_load_dynamic / ENGINE_by_id block
shown in the verified readme.md).sha1 / sha256 /
sha512 paths.Do not load this skill for users building a new
SHA-pipeline from scratch — route to
../../libs/doca-sha/SKILL.md.
Do not load this skill for users wanting algorithms the
engine does not implement (MD5, SHA-3, SHA-224, HMAC-SHA,
streaming/incremental SHA via EVP_DigestUpdate chains
that the engine treats as one-shot only).
This is a thin loader. Substantive material lives in two companion files:
CAPABILITIES.md — what the engine offloads (verified:
one-shot SHA-1, SHA-256, SHA-512 via the OpenSSL
EVP_Digest high-level interface), what it does NOT
offload (anything else — including SHA-224, MD5,
SHA-3, HMAC-SHA, and any chained
EVP_DigestInit_ex / EVP_DigestUpdate /
EVP_DigestFinal_ex pattern that the engine implements
by buffering and then calling DOCA SHA in one shot at
Final), the engine-vs-library selection rule, the
message-size-window rule for when offload is a perf
win, the verified ctrl-cmd surface (set_pci_addr),
the version overlay (OpenSSL ≥ 1.1.1; the engine's
shipped tests cover OpenSSL 1.1.1f and OpenSSL 3.0.2
per the readme.md; OpenSSL 3.x deprecates the ENGINE
API but still supports it via the legacy code path),
the layered error taxonomy, the observability surface
(the "prove offload engaged" pattern using the
SHA-224 negative test and -engine_impl), and the
safety overlay.TASKS.md — step-by-step workflows for the in-scope
task verbs: install, configure (PCIe address
selection — the engine defaults to 03:00.0 and
exposes the set_pci_addr ctrl-cmd plus a build-time
override per the shipped test_cmdline_mode/readme.md),
build (the meson flow), modify (refuses source
patching; modify the load-time invocation and the
PCIe address instead), run (load the engine via
openssl engine dynamic; the verification pattern;
the OpenSSL programmatic ENGINE_load_dynamic block),
test (the "prove the engine ran" SHA-224 negative
test; the openssl speed perf comparison; the
message-size window characterization), debug (walk
the error taxonomy layer by layer), use (the
engine-vs-library decision for the user's specific
pipeline), plus a Deferred task verbs block.The skill assumes a host where DOCA is already installed,
OpenSSL ≥ 1.1.1 is present (libssl-dev or equivalent),
and the deploying user can access the selected DOCA SHA PCIe device. Verify
device visibility and run the engine-load smoke as that same user before
integration; if either fails with a permission error, stop and route to
doca-setup rather than guessing a group, ACL, or sudo policy.
This skill is agent guidance, not a samples or scripts bundle. It deliberately does not contain — and pull requests should not add:
readme.md (the ENGINE_load_dynamic /
ENGINE_by_id / ENGINE_ctrl_cmd_string /
ENGINE_init / ENGINE_set_default_digests sequence,
cross-referenced into TASKS.md ## run).
The shipped readme is the worked example.samples/, bindings/, or reference/
subtree. This is a thin loader for a shipped
shared-object; substantive material lives in the
shipped readme.md and the doca-sha library docs.openssl speed comparison
pattern in TASKS.md ## test is the
way to capture it on the user's actual hardware;
quoting a number from memory is the cross-platform
failure mode this skill exists to prevent.openssl speed output format.SKILL.md first to confirm the user's
question is in scope (the user actually has an
existing OpenSSL-based pipeline and wants to offload
to DOCA SHA without code changes; if the user is
building from scratch, route to
../../libs/doca-sha/).install,
configure, build, modify, run, test,
debug, use — see TASKS.md.../../libs/doca-sha/SKILL.md —
the underlying DOCA SHA library. The engine is a
thin OpenSSL-ENGINE wrapper around doca-sha; when the
user needs fine-grained control over the SHA task
surface (partial-hash, custom buffer permissions,
cap-query for unusual message sizes), the library is
the right answer. The engine wraps the one-shot
task; the library exposes both one-shot and partial-
hash per
../../libs/doca-sha/CAPABILITIES.md#capabilities-and-modes.doca-version — the
canonical version-detection chain. The engine has a
TWO-axis version overlay (DOCA-side and OpenSSL-side);
the version skill carries the four-way match rule
this skill layers on top of.doca-debug — the
cross-cutting debug ladder. The engine surfaces its
own error taxonomy; when the cause is below DOCA
(driver, firmware), the taxonomy hands off here.doca-setup — env
preparation, install verification, the libssl-dev
install path, and the NGC DOCA container path.doca-public-knowledge-map —
routing to the public DOCA SHA documentation set on
docs.nvidia.com/doca/sdk/ and to the OpenSSL
ENGINE / openssl-engine upstream documentation on
openssl.org.doca-hardware-safety —
the bundle-wide hardware-safety meta-policy. The
engine binds to a specific PCIe device; the
set_pci_addr ctrl is the artifact-specific overlay,
but any host-side change underneath (firmware burn,
BFB reflash) runs through the meta-policy.© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 7 other files in skills/doca-sha-offload-engine of NVIDIA/skills.
Open the folder on GitHubat commit 0e0d506
Doca Sha Offload Engine next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Doca Sha Offload Engine this skillNVIDIA/skills | 3.5k | — | ~4k | Automated safety check: Pass | Apache-2.0 | |
| LLM Torch Profiler Analysissgl-project/sglang | 37k | 2 repos | ~6.4k | Automated safety check: Pass | Apache-2.0 | |
| Skill InspectorNVIDIA/SkillSpector | 20k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Embeddings via 9Routerdecolua/9router | 30k | — | ~604 | Automated safety check: Pass | MIT | |
| NEAR AI Cloud Private Inferenceinternet-court/internet-court-skill | 6.4k | 2 repos | ~1.3k | Automated safety check: Pass | Custom licence | |
| Nemoclaw Maintainer Normalize Title TagsNVIDIA/NemoClaw | 23k | — | ~693 | Automated safety check: Pass | Apache-2.0 |
sgl-project/sglang
Unified LLM torch-profiler triage skill for sglang, vllm, TensorRT-LLM, and TokenSpeed.
NVIDIA/SkillSpector
Decides whether an agent skill is safe to install by combining a SkillSpector static scan with the agent's own source review, ending in APPROVE, CAUTION or REJECT.
decolua/9router
Generates vector embeddings through the 9Router /v1/embeddings endpoint, using models from providers such as OpenAI, Gemini, Mistral and Voyage for RAG and semantic search.
internet-court/internet-court-skill
Shows how to call NEAR AI Cloud through an OpenAI-compatible API and verify that inference ran in a TEE, using attestation checks and signed chat responses.
NVIDIA/NemoClaw
Remove bracketed NemoClaw tags from GitHub issue and PR titles.
NVIDIA/Megatron-LM
Walks an agent through working inside the Megatron-LM CI container and changing dependencies with uv, so lock files resolve the same locally and in CI.
NVIDIA/skills
A skill your agent uses when the user wants to deploy, run, debug, tear down, or call the REST API of the RTVI-CV 2D detection / tracking microservice.
NVIDIA/skills
Generates, validates, compares and explains HOLOLINK_def.svh macro files for the HSB IP, using bundled Python scripts and asking before it writes anything.
NVIDIA/skills
Runs and validates an end-to-end Mission Control demo in a locally installed Isaac Sim, with a Nova Carter robot driven through a Python server.
NVIDIA/skills
Orchestrates defect image generation for PCBA, metal surface and glass inspection with NVIDIA Cosmos AnomalyGen on OSMO, from cold-start Day 0 to real-photo Day 1 labeling.
NVIDIA/skills
Orchestrates video data augmentation and auto-labeling workflows on OSMO, from flow selection and preflight checks to submission, monitoring and output download.
NVIDIA/skills
Runs NVIDIA TAO Data Services KPI analysis on object detection results, comparing predictions to ground truth and writing per-class precision, recall and AP to a CSV.
Works with
A skill your agent uses when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVPDigest) onto DOCA SHA…. Doca Sha Offload Engine is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Use this skill when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVPDigest) onto DOCA SHA hardware without rewriting against doca-sha.
Doca Sha Offload Engine fits situations like: wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1; SHA-512 (EVPDigest) onto DOCA SHA hardware without rewriting against doca-sha; even when the user does not say DOCA SHA Offload Engine; openSSL ENGINE — typical implicit phrasings: speed up openssl SHA on BlueField.
Run `npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a claude-code`. Or copy the skill folder (skills/doca-sha-offload-engine in NVIDIA/skills) into .claude/skills/doca-sha-offload-engine in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a codex`. Or copy the skill folder (skills/doca-sha-offload-engine in NVIDIA/skills) into .agents/skills/doca-sha-offload-engine in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill doca-sha-offload-engine -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/doca-sha-offload-engine, .gemini/skills/doca-sha-offload-engine, .github/skills/doca-sha-offload-engine and .opencode/skills/doca-sha-offload-engine in your project.
Going by SKILL.md and its folder, Doca Sha Offload Engine needs the command-line tools its instructions call (openssl). Our summary lists: Python 3. Compatibility (from SKILL.md): Requires DOCA SDK installed at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField DPU or ConnectX NIC attached, plus OpenSSL ≥ 1.1.1 and libssl-dev (or distro equivalent) on the build host. The engine ships under /opt/mellanox/doca/tools/doca_sha_offload_engine/ as libdoca_sha_offload_engine.so; reads the user's local install via `pkg-config doca-sha` and inspects /opt/mellanox/doca/{lib,include,samples,applications}. .
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Doca Sha Offload Engine is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Doca Sha Offload Engine: LLM Torch Profiler Analysis (sgl-project/sglang, 37k stars), Skill Inspector (NVIDIA/SkillSpector, 20k stars), Embeddings via 9Router (decolua/9router, 30k stars) and NEAR AI Cloud Private Inference (internet-court/internet-court-skill, 6.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,534 GitHub stars. The repository holds 380 skills in this directory. The repository was last updated on October 7, 2026.
Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.