Finishing a Development Branch
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
A skill your agent uses when the user is doing hands-on NVMe-over-Fabrics storage-target work on a BlueField DPU or ConnectX NIC with DOCA STA — standing up a docasta DOCA Core context that…
$ npx skills add NVIDIA/skills --skill doca-sta -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills doca-sta --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-sta .claude/skills/doca-sta && 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-sta" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sta into .claude/skills/doca-sta/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sta", 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-staType 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-sta -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills doca-sta --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-sta .agents/skills/doca-sta && 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-sta" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sta into .agents/skills/doca-sta/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sta", 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-sta -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills doca-sta --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-sta .cursor/skills/doca-sta && 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-sta" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sta into .cursor/skills/doca-sta/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sta", 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-sta--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-sta -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills doca-sta --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-sta .gemini/skills/doca-sta && 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-sta" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sta into .gemini/skills/doca-sta/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sta", 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-staInstalls 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-sta -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-sta .github/skills/doca-sta && 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-sta" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sta into .github/skills/doca-sta/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sta", 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-sta -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-sta --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-sta .opencode/skills/doca-sta && 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-sta" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-sta into .opencode/skills/doca-sta/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-sta", 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-staA skill your agent uses when the user is doing hands-on NVMe-over-Fabrics storage-target work on a BlueField DPU or ConnectX NIC with DOCA STA — standing up a docasta DOCA Core context that…
Doca Sta is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Use this skill when the user is doing hands-on NVMe-over-Fabrics storage-target work on a BlueField DPU or ConnectX NIC with DOCA STA — standing up a docasta DOCA Core context that accelerates the target-side NVMe-oF data path over RDMA, defining docastasubsystem targets (NQN + namespaces) backed by local NVMe-PCI backend disks (docastabe), checking device support via docastacapissupported, sizing the per-connection I/O queues, or debugging DOCAERROR from a STA call. Trigger even when the user does not say "DOCA…
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. Reads the user's…
It sits in Development. 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.
No scripts in the folder and no shell commands in SKILL.md.
From 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. Reads the user's local install via `pkg-config doca-sta` (and `pkg-config doca-rdma` for the NVMe-over-RDMA transport) and inspects /opt/mellanox/doca/{lib,include,samples,applications}.
From compatibility in the SKILL.md frontmatter.
Doca Sta loads about 4k tokens when it runs. Until then it costs about 248 tokens; SKILL.md has 1,742 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). 1,742 words, ~3,955 tokens.
.claude/skills/doca-sta/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 skill assumes DOCA is already installed and
the user is doing hands-on NVMe-over-Fabrics storage-target work on
a BlueField-class device with DOCA. Open TASKS.md if
the user wants to do something (configure / modify / build / run
/ test / debug); open CAPABILITIES.md when the
question is what can DOCA STA express on this version. If the
user has not installed DOCA yet, route to
doca-setup first. If the user is
asking "is this an NVMe-oF initiator/host transport?", the
answer is no — doca-sta accelerates the target side: it presents
NVMe-oF doca_sta_subsystem targets backed by local NVMe-PCI
disks; the model lives in
CAPABILITIES.md ## Capabilities and modes.
The CLASSES of DOCA STA questions this skill is built to answer, each with one worked example. The agent should treat the class as the load-bearing piece — the worked example is a single instance.
doca_sta_subsystem (NQN) with one namespace backed by a local
NVMe-PCI disk (doca_sta_be) and accept NVMe-over-RDMA
connections from a remote initiator". Answered by the
target-model-and-lifecycle
workflow in TASKS.md ## configure +
CAPABILITIES.md ## Capabilities and modes
target-object table.doca_sta_cap_is_supported against a
doca_devinfo) in
CAPABILITIES.md ## Capabilities and modesTASKS.md ## configure.CAPABILITIES.md ## Capabilities and modesTASKS.md ## configure which gates on
the matching doca_sta_get_max_* query (e.g.
doca_sta_get_max_qps, doca_sta_get_max_io_queue_size).CAPABILITIES.md ## Safety policyTASKS.md ## configure step 1, which
routes the steering side to
doca-flow and the RDMA substrate
to doca-rdma.CAPABILITIES.md ## Version compatibility,
which cross-links the canonical detection chain in
doca-version and adds the
STA-specific cap-query rule (pkg-config --modversion doca-sta
is the build-time anchor; the runtime doca_sta_cap_is_supported
query is the truth).DOCA_ERROR_* from a STA call mean and which
layer caused it?" — worked example: "DOCA_ERROR_IO_FAILED
on a submitted NVMe read I/O against a target I can ping".
Answered by the STA overlay on the cross-library taxonomy in
CAPABILITIES.md ## Error taxonomyTASKS.md ## debug that escalates to
doca-debug.This skill serves external developers building NVMe-over-Fabrics
storage targets that consume DOCA STA on BlueField — i.e., users
whose code calls doca_sta_* (directly in C/C++, or through
FFI/bindings from another language) to accelerate the target-side
data path of an NVMe-oF target on the BlueField hardware: presenting
doca_sta_subsystem targets (NQN + namespaces) backed by local
NVMe-PCI disks (doca_sta_be) to remote initiators over RDMA. The
skill is not for NVIDIA developers contributing to DOCA STA
itself, and it is not for initiator/host-side NVMe stacks.
Language scope. DOCA STA ships as a C library with
pkg-config module name doca-sta. DOCA STA ships no public
samples — it is absent from the DOCA libraries /
extension_libraries sample profiles — so the worked examples in
TASKS.md build against the public headers directly rather than
modify a shipped sample. C and C++ consumers are the canonical
case. Other-language
consumers (Rust, Go, Python, …) consume the same *.so through
FFI or language-specific bindings; the skill's contribution in
that case is to keep the target-model, lifecycle,
capability-discovery, queue-pair shape, substrate-dependency,
and error-taxonomy guidance language-neutral, and to route the
agent to the public C ABI as the authoritative surface that any
wrapper will eventually call.
Load this skill when the user is doing hands-on DOCA STA work, in any language. Concretely:
doca_sta instance on a doca_dev opened
against a BlueField PF / SF and configuring the NVMe-oF
target subsystems before doca_ctx_start().doca_sta_subsystem (NQN +
namespaces) and doca_sta_be backend controllers (local
NVMe-PCI disks) — and accepting NVMe-oF connections (admin
queue plus N I/O queues per connection) on the target side as
remote initiators connect over RDMA CM.doca_sta_set_*
family, checking device support via doca_sta_cap_is_supported,
and querying sizing limits via the doca_sta_get_max_* family
(max I/O queue depth, max number of queue pairs, max I/O size,
max subsystems, max namespaces per subsystem, max backends).doca-rdma substrate and uses RDMA CM for
connection establishment — for the target's I/O queues.doca-flow, not doca-sta.DOCA_ERROR_* returned from a STA call (lifecycle
vs. capability vs. transport-layer I/O failure vs.
driver-below) and the per-queue events on the DOCA Core
progress engine.Do not load this skill for general DOCA orientation, install
of DOCA itself, raw RDMA data movement (use
doca-rdma), raw packet I/O on
Ethernet queues (use doca-eth),
flow-rule programming (use doca-flow),
or initiator/host-side NVMe stack development
(SPDK or kernel-nvme own that, not this skill). For DOCA
documentation orientation, use
doca-public-knowledge-map.
This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive STA-specific material lives in two companion files:
CAPABILITIES.md — what DOCA STA can express on this
version: the target object model (doca_sta_subsystem /
namespaces / doca_sta_be backend NVMe-PCI disks),
the NVMe queue-pair shape (admin queue + I/O queues over RDMA),
the RDMA-only transport,
the capability-query surface (doca_sta_cap_is_supported plus
the doca_sta_get_max_* sizing queries), the STA
error taxonomy (mapped onto the cross-library DOCA_ERROR_*
set), the observability surface (per-queue progress engine
events, capability snapshots), and the safety policy that
gates substrate-library, permission, and steering
preconditions.TASKS.md — step-by-step workflows for the six in-scope
STA verbs: configure, modify, build, run, test,
debug. Plus a Deferred task verbs block that points
out-of-scope questions at the right next skill, and a
Command appendix of the recurring commands the agent
reaches for.The skill assumes a BlueField (with DOCA installed at the
standard location) plus a remote NVMe-oF initiator reachable on
the fabric to connect into the accelerated target, and one or
more local NVMe-PCI disks to back the target's namespaces. It
does not cover installing
DOCA — that path goes through
doca-setup. It does not cover
initiator/host-side NVMe stacks (SPDK bdev_nvme, kernel nvme
host) or NVMe protocol semantics above the accelerated target
data path — those are out of scope.
This skill is agent guidance, not a samples or templates bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
/opt/mellanox/doca/samples/doca_sta/ directory, and STA is
absent from the libraries / extension_libraries sample
profiles. The authoritative surface is the public headers under
$(pkg-config --variable=includedir doca-common) plus the public
DOCA STA guide; the agent builds against those directly rather
than modifying a shipped sample, per the
TASKS.md ## modify workflow.bdev_nvme,
the kernel nvme host, and any initiator-side NVMe stack are
upstream projects out of scope for this skill — DOCA STA is
target-side acceleration, not an initiator transport provider.meson.build, CMakeLists.txt,
Cargo.toml, …) parked inside the skill. The agent
constructs the build manifest in the user's project
directory against the user's installed DOCA, where
pkg-config --modversion doca-sta is the source of truth.samples/, bindings/, or reference/ subtree of any
kind. A mock or incomplete artifact in this skill's tree,
even one labeled "reference", is misleading: users will
read it as buildable.SKILL.md first to confirm the user's question
is in scope.Both companion files cross-link to each other,
doca-version for the canonical
version-handling rules,
doca-rdma for the RDMA substrate
that NVMe-over-RDMA transport lands on,
doca-flow for the steering rules
that direct NVMe traffic to STA-managed queues, and
doca-public-knowledge-map
whenever the right answer is "look it up in the public docs or
the installed package layout" rather than "STA-specific
guidance".
doca-public-knowledge-map —
the routing table for every public DOCA documentation source
and the on-disk layout of an installed DOCA package. The
STA URL slug is DOCA-STA.doca-setup — env preparation,
install verification, BlueField mode checks, and the
permission / group-membership requirements for opening a
doca_dev. This skill assumes its preconditions are
satisfied.doca-version — canonical
DOCA version-handling rules. This skill's ## Version compatibility cross-links the four-way match rule and adds
only the STA-specific overlay (STA target-acceleration
availability windows, NVMe-oF feature-set device-conditional
support).doca-structured-tools-contract —
the bundle's structured-tools precedence rule (detect /
prefer / fall back / report). The Command appendix in
TASKS.md honors this contract.doca-programming-guide —
general DOCA programming patterns shared by every library:
the canonical pkg-config + meson build pattern, the
universal modify-a-shipped-sample first-app workflow, the
universal lifecycle, the cross-library DOCA_ERROR_*
taxonomy, and the program-side debug order. This skill
layers STA specifics on top.doca-rdma — the RDMA substrate
that NVMe-over-RDMA transport lands on. STA hides most of
the RDMA queue-pair details from the consumer, but the user
still needs doca-rdma linked in and the device's RDMA
capabilities discoverable for the NVMe-over-RDMA path to
work.doca-eth — the queue-pair
shape that STA's per-connection queue model echoes. Reach
here if the user is asking general questions about how
DOCA exposes queue-pairs that don't have an STA-specific
answer.doca-flow — the steering
surface that decides which NVMe-oF packets land on which
STA-managed queue. DOCA STA does not program steering
itself; an NVMe-oF target whose connections never come up
is often a missing or wrong Flow rule, not a STA bug.doca-debug — the
cross-cutting debug ladder (install / version / build /
link / runtime / program / driver). STA-specific debug
(transport-type mismatches, queue-depth oversize,
IO-failed transport errors) overlays on top of that
ladder.© 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-sta of NVIDIA/skills.
Open the folder on GitHubat commit 0e0d506
Doca Sta 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 Sta this skillNVIDIA/skills | 3.5k | — | ~4k | Automated safety check: Pass | Apache-2.0 | |
| Finishing a Development Branchobra/superpowers | 296k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Typescript Advanced Typesrolling-scopes/rsschool-app | 10k | 24 repos | ~4.2k | Automated safety check: Pass | MPL-2.0 | |
| PR Babysitteropeninterpreter/openinterpreter | 69k | 3 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 5 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Greplooponyx-dot-app/onyx | 32k | 4 repos | ~3.3k | Automated safety check: Pass | MIT |
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
rolling-scopes/rsschool-app
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications.
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
onyx-dot-app/onyx
Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments.
akash-network/node
Behavioral guidelines to reduce common LLM coding mistakes. An agent skill from akash-network/node.
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.
Categories
A skill your agent uses when the user is doing hands-on NVMe-over-Fabrics storage-target work on a BlueField DPU or ConnectX NIC with DOCA STA — standing up a docasta DOCA Core context that…. Doca Sta is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Use this skill when the user is doing hands-on NVMe-over-Fabrics storage-target work on a BlueField DPU or ConnectX NIC with DOCA STA — standing up a docasta DOCA Core context that accelerates the target-side NVMe-oF data path over RDMA, defining docastasubsystem targets (NQN + namespaces) backed by local NVMe-PCI backend disks (docastabe), checking device support via docastacapissupported, sizing the per-connection I/O queues, or debugging DOCAERROR from a STA call.
Doca Sta fits situations like: the user is doing hands-on NVMe-over-Fabrics storage-target work on a BlueField DPU; connectX NIC with DOCA STA — standing up a docasta DOCA Core context that accelerates the target-side NVMe-oF data path over RDMA; defining docastasubsystem targets (NQN + namespaces) backed by local NVMe-PCI backend disks (docastabe); checking device support via docastacapissupported.
Run `npx skills add NVIDIA/skills --skill doca-sta -a claude-code`. Or copy the skill folder (skills/doca-sta in NVIDIA/skills) into .claude/skills/doca-sta in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill doca-sta -a codex`. Or copy the skill folder (skills/doca-sta in NVIDIA/skills) into .agents/skills/doca-sta 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-sta -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-sta, .gemini/skills/doca-sta, .github/skills/doca-sta and .opencode/skills/doca-sta in your project.
SKILL.md names no scripts, command-line tools or credentials: Doca Sta is instructions for the agent only. 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. Reads the user's local install via `pkg-config doca-sta` (and `pkg-config doca-rdma` for the NVMe-over-RDMA transport) 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 Sta 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 Sta: Finishing a Development Branch (obra/superpowers, 296k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars) and Code Review Checklist (shareAI-lab/learn-claude-code, 78k 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.