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 DOCA DMA programming — bringing up a docadma context, configuring the single docadmataskmemcpy task type, sizing buffers via the…
$ npx skills add NVIDIA/skills --skill doca-dma -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills doca-dma --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-dma .claude/skills/doca-dma && 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-dma" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-dma into .claude/skills/doca-dma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-dma", 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-dmaType 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-dma -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills doca-dma --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-dma .agents/skills/doca-dma && 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-dma" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-dma into .agents/skills/doca-dma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-dma", 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-dma -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills doca-dma --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-dma .cursor/skills/doca-dma && 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-dma" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-dma into .cursor/skills/doca-dma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-dma", 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-dma--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-dma -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills doca-dma --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-dma .gemini/skills/doca-dma && 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-dma" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-dma into .gemini/skills/doca-dma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-dma", 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-dmaInstalls 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-dma -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-dma .github/skills/doca-dma && 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-dma" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-dma into .github/skills/doca-dma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-dma", 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-dma -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-dma --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-dma .opencode/skills/doca-dma && 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-dma" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-dma into .opencode/skills/doca-dma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-dma", 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-dmaA skill your agent uses when the user is doing hands-on DOCA DMA programming — bringing up a docadma context, configuring the single docadmataskmemcpy task type, sizing buffers via the…
Doca Dma 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 DOCA DMA programming — bringing up a docadma context, configuring the single docadmataskmemcpy task type, sizing buffers via the docadmacaptaskmemcpy queries, setting LOCALREADONLY / LOCALREADWRITE permissions on source / destination docammap regions (plus docammapexport for cross-peer copies), driving the progress engine, or debugging DOCAERROR returns. Trigger even when the user does not explicitly mention "DOCA DMA" or "docammap" — typical implicit phrasings…
Its SKILL.md is about 3.3k 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.
Hosts in commands or code, which the agent is likely to contact:
docs.nvidia.comFrom 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-dma` and inspects /opt/mellanox/doca/{lib,include,samples,applications}.
From compatibility in the SKILL.md frontmatter.
Doca Dma loads about 3.3k tokens when it runs. Until then it costs about 252 tokens; SKILL.md has 1,442 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). 1,442 words, ~3,326 tokens.
.claude/skills/doca-dma/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 DMA work on a BlueField /
ConnectX / host with DOCA. Open TASKS.md if the user
wants to do something (configure / build / modify / run / test /
debug); open CAPABILITIES.md when the question
is what can DMA express on this version. If the user has not
installed DOCA yet, route to
doca-setup first. If the user is
not sure DMA is even the right library — the data has to traverse
the network, or the flow is small messages between two processes —
read the path-selection rule in
CAPABILITIES.md ## Capabilities and modes
before configuring anything.
The CLASSES of DMA 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.
TASKS.md ## configure +
CAPABILITIES.md ## Capabilities and modes
task-type table.doca_dma_task_memcpy". Answered by the capability-query rule
(doca_dma_cap_task_memcpy_get_max_buf_size, plus
_get_max_buf_list_len for scatter-gather) in
CAPABILITIES.md ## Capabilities and modesTASKS.md ## configure.DOCA_ERROR_NOT_PERMITTED on the first submit". Answered by the
source / destination permission matrix in
CAPABILITIES.md ## Safety policyTASKS.md ## test.CAPABILITIES.md ## Capabilities and modes## Related skills.doca_dma_task_memcpy available on DOCA 2.6 against this
ConnectX-6". Answered by the version-compatibility overlay in
CAPABILITIES.md ## Version compatibility,
which cross-links the canonical detection chain in
doca-version, plus the
capability-query rule in
CAPABILITIES.md ## Capabilities and modes.DOCA_ERROR_* from a DMA call mean and which
layer caused it?" — worked example: "DOCA_ERROR_AGAIN from
doca_task_submit on a doca_dma_task_memcpy". Answered by
the DMA overlay on the cross-library taxonomy in
CAPABILITIES.md ## Error taxonomyTASKS.md ## debug that escalates to
doca-debug.This skill serves external developers building applications
that consume the DOCA DMA library — i.e., users whose code calls
doca_dma_* (directly in C/C++, or through FFI/bindings from
another language) to copy bytes between two doca_mmap regions
using the BlueField DMA engine instead of the host CPU. It is
not for NVIDIA developers contributing to DOCA DMA itself.
Language scope. DOCA DMA ships as a C library with
pkg-config module name doca-dma. The shipped samples are
written in C. C and C++ consumers are the canonical case and the
worked examples in TASKS.md assume that path. 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 lifecycle, capability-discovery,
permission, error-taxonomy, and path-selection 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 DMA work, in any language. Concretely:
doca_dma context on a doca_dev and
configuring the memcpy task type via
doca_dma_task_memcpy_set_conf before doca_ctx_start().doca_mmap regions for
a memcpy, including the per-side permission flags
(DOCA_ACCESS_FLAG_LOCAL_READ_ONLY on the source,
DOCA_ACCESS_FLAG_LOCAL_READ_WRITE on the destination) and,
for cross-peer copies, the doca_mmap_export_* step.doca_dma_cap_task_memcpy_* query family
(_is_supported, _get_max_buf_size,
_get_max_buf_list_len) before sizing any buffer or assuming
scatter-gather is available.doca_dma_task_memcpy tasks against a DOCA progress
engine and reacting to per-task completion events.DOCA_ERROR_* returned from a DMA call (lifecycle
vs. permission vs. capability vs. would-block) and the
per-task completion status reported on the progress engine.Do not load this skill for general DOCA orientation, install
of DOCA itself, or non-DMA library questions. For those, 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 DMA-specific material lives in two companion files:
CAPABILITIES.md — what DMA can express on this version: the
single doca_dma_task_memcpy task type and its scatter-gather
buffer-list shape, the capability-query surface
(doca_dma_cap_task_memcpy_*), the DMA error taxonomy (mapped
onto the cross-library DOCA_ERROR_* set), the observability
surface (per-task completion events on the progress engine),
the source / destination mmap permission policy, and the
path-selection rule against the adjacent libraries
(RDMA / Comch / CPU memcpy).TASKS.md — step-by-step workflows for the six in-scope DMA
verbs: configure, build, modify, run, test, debug.
Plus a Deferred task verbs block that points out-of-scope
questions at the right next skill.The skill assumes a host or BlueField where DOCA is already
installed at the standard location and the user has the
privileges their public install profile expects. It does not
cover installing DOCA — that path goes through
doca-setup.
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_dma/<name>/ and
the DMA Copy reference application reachable via
doca-public-knowledge-map.
The agent's job is to route the user to those files and
prescribe a minimum-diff modification on them via the universal
modify-a-sample workflow in
doca-programming-guide,
layered with the DMA-specific overrides in
TASKS.md ## modify.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-dma 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, and
doca-public-knowledge-map
whenever the right answer is "look it up in the public docs or
the installed package layout" rather than "DMA-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 DMA
URL is https://docs.nvidia.com/doca/sdk/DOCA-DMA/index.html;
the canonical reference application is DMA Copy.doca-setup — env preparation,
install verification, and the I have no install yet path
with the public NGC DOCA container. 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 + detection
chain and adds at most one DMA-specific overlay rule.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 DMA specifics on
top.doca-rdma — the right library when
the copy has to traverse the network. This skill's
path-selection rule routes to RDMA when DMA is not the
answer.doca-comch — the right library
when the flow is producer / consumer messaging between a host
and DPU process pair, rather than a raw mmap-to-mmap copy.doca-debug — the cross-cutting
debug ladder (install / version / build / link / runtime /
program / driver). DMA-specific debug (lifecycle violations,
permission mismatches, oversize-buffer rejections) 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-dma of NVIDIA/skills.
Open the folder on GitHubat commit 0e0d506
Doca Dma 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 Dma this skillNVIDIA/skills | 3.5k | — | ~3.3k | 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 DOCA DMA programming — bringing up a docadma context, configuring the single docadmataskmemcpy task type, sizing buffers via the…. Doca Dma 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 DOCA DMA programming — bringing up a docadma context, configuring the single docadmataskmemcpy task type, sizing buffers via the docadmacaptaskmemcpy queries, setting LOCALREADONLY / LOCALREADWRITE permissions on source / destination docammap regions (plus docammapexport for cross-peer copies), driving the progress engine, or debugging DOCAERROR returns.
Doca Dma fits situations like: the user is doing hands-on DOCA DMA programming — bringing up a docadma context; configuring the single docadmataskmemcpy task type; sizing buffers via the docadmacaptaskmemcpy queries; setting LOCALREADONLY / LOCALREADWRITE permissions on source / destination docammap regions (plus docammapexport for cross-peer copies).
Run `npx skills add NVIDIA/skills --skill doca-dma -a claude-code`. Or copy the skill folder (skills/doca-dma in NVIDIA/skills) into .claude/skills/doca-dma in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill doca-dma -a codex`. Or copy the skill folder (skills/doca-dma in NVIDIA/skills) into .agents/skills/doca-dma 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-dma -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-dma, .gemini/skills/doca-dma, .github/skills/doca-dma and .opencode/skills/doca-dma in your project.
SKILL.md names no scripts, command-line tools or credentials: Doca Dma 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-dma` and inspects /opt/mellanox/doca/{lib,include,samples,applications}. .
SKILL.md names 1 domain. In commands or code: docs.nvidia.com; the agent is likely to contact it when it follows the instructions. 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 Dma 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 3.3k tokens (SKILL.md is roughly 13k 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 Dma: 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.