Monitor CI
nrwl/nx
Monitor Nx Cloud CI pipeline and handle self-healing fixes. An agent skill from nrwl/nx.
A skill your agent uses when the user is doing hands-on deployment, tuning, or evaluation of the DOCA-shipped Zero-Touch RoCE RTT-based Congestion Control (ZTR RTTCC) reference algorithm on a…
$ npx skills add NVIDIA/skills --skill doca-pcc-ztr-rttcc-algo -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills doca-pcc-ztr-rttcc-algo --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-pcc-ztr-rttcc-algo .claude/skills/doca-pcc-ztr-rttcc-algo && 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-pcc-ztr-rttcc-algo" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-pcc-ztr-rttcc-algo into .claude/skills/doca-pcc-ztr-rttcc-algo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-pcc-ztr-rttcc-algo", 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-pcc-ztr-rttcc-algoType 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-pcc-ztr-rttcc-algo -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills doca-pcc-ztr-rttcc-algo --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-pcc-ztr-rttcc-algo .agents/skills/doca-pcc-ztr-rttcc-algo && 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-pcc-ztr-rttcc-algo" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-pcc-ztr-rttcc-algo into .agents/skills/doca-pcc-ztr-rttcc-algo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-pcc-ztr-rttcc-algo", 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-pcc-ztr-rttcc-algo -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills doca-pcc-ztr-rttcc-algo --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-pcc-ztr-rttcc-algo .cursor/skills/doca-pcc-ztr-rttcc-algo && 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-pcc-ztr-rttcc-algo" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-pcc-ztr-rttcc-algo into .cursor/skills/doca-pcc-ztr-rttcc-algo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-pcc-ztr-rttcc-algo", 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-pcc-ztr-rttcc-algo--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-pcc-ztr-rttcc-algo -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills doca-pcc-ztr-rttcc-algo --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-pcc-ztr-rttcc-algo .gemini/skills/doca-pcc-ztr-rttcc-algo && 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-pcc-ztr-rttcc-algo" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-pcc-ztr-rttcc-algo into .gemini/skills/doca-pcc-ztr-rttcc-algo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-pcc-ztr-rttcc-algo", 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-pcc-ztr-rttcc-algoInstalls 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-pcc-ztr-rttcc-algo -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-pcc-ztr-rttcc-algo .github/skills/doca-pcc-ztr-rttcc-algo && 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-pcc-ztr-rttcc-algo" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-pcc-ztr-rttcc-algo into .github/skills/doca-pcc-ztr-rttcc-algo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-pcc-ztr-rttcc-algo", 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-pcc-ztr-rttcc-algo -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-pcc-ztr-rttcc-algo --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-pcc-ztr-rttcc-algo .opencode/skills/doca-pcc-ztr-rttcc-algo && 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-pcc-ztr-rttcc-algo" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-pcc-ztr-rttcc-algo into .opencode/skills/doca-pcc-ztr-rttcc-algo/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-pcc-ztr-rttcc-algo", 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-pcc-ztr-rttcc-algoA skill your agent uses when the user is doing hands-on deployment, tuning, or evaluation of the DOCA-shipped Zero-Touch RoCE RTT-based Congestion Control (ZTR RTTCC) reference algorithm on a…
Doca Pcc Ztr Rttcc Algo 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 deployment, tuning, or evaluation of the DOCA-shipped Zero-Touch RoCE RTT-based Congestion Control (ZTR RTTCC) reference algorithm on a BlueField-3 DPA — wiring docapccdevztrrttccalgo into the shipped DOCA PCC sample, picking a variant (vanilla / PM / RX-rate / multipath / window-probeless) at DPACC build time, tuning host-set parameters, or diagnosing DOCAPCCDEVSTATUSFAIL from the algorithm. Trigger even when the user does not say 'DOCA PCC' or 'ZTR RTTCC' — typical…
Its SKILL.md is about 4.8k 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-3 DPU exposing the DPA processor, the firmware…
It sits in DevOps & Cloud. 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 14a98ae. 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.
Links to these hosts (documentation or services it may open):
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-3 DPU exposing the DPA processor, the firmware custom-PCC slot enabled, a matched-version DPACC compiler, and live RoCE-v2 traffic on the attached port. Reads `pkg-config doca-pcc-ztr-rttcc-algo` and inspects /opt/mellanox/doca/{lib,include,applications/pcc}.
From compatibility in the SKILL.md frontmatter.
Doca Pcc Ztr Rttcc Algo loads about 4.8k tokens when it runs. Until then it costs about 259 tokens; SKILL.md has 2,082 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 14a98ae, republished under its Apache-2.0 licence (© NVIDIA). 2,082 words, ~4,755 tokens.
.claude/skills/doca-pcc-ztr-rttcc-algo/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, the user's BlueField has a DPA processor that
the host can see through DOCA (a BlueField-3-generation
device per the README), the BlueField firmware has the
custom-PCC slot enabled, the DPACC compiler is installed at
a matched version per the DOCA Compatibility Policy, and the
user is doing hands-on deployment of the DOCA-shipped ZTR
RTTCC reference algorithm on a BlueField port that
already carries RoCE-v2 traffic — i.e. either deploying it
as the no-config-required baseline, tuning its documented
parameters, or evaluating it against a custom algorithm the
user intends to write. Open TASKS.md if the
user wants to do something (install / configure / build /
modify / run / test / debug / use); open
CAPABILITIES.md when the question is
what does the algorithm express, what are its variants and
parameters, what does it ship vs not ship. If the user has
not installed DOCA yet, route to
doca-setup first; if the user
has not stood up the host-side doca-pcc framework yet,
route to doca-pcc first (this
algorithm is a library consumed by the PCC framework, not
a standalone program); if the user only wants to inspect
PCC counters at runtime without changing the running
algorithm, route to
doca-pcc-counters;
if the user wants to write their own algorithm from
scratch, that is the doca-pcc library plus the public
PCC programming guide — this skill is for the shipped
reference algorithm specifically.
The CLASSES of ZTR RTTCC 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.
CAPABILITIES.md ## Capabilities and modes
("when to use the reference vs custom") + the env
preconditions in
TASKS.md ## install./opt/mellanox/doca/applications/pcc
is already building from sample sources; what do I
change so the user algo callback dispatches to
doca_pcc_dev_ztr_rttcc_algo under a chosen algo
slot?". Answered by the integration sequence in
CAPABILITIES.md ## Capabilities and modesTASKS.md ## modify.doca_pcc_dev_ztr_rttcc_algo but the device-
side source ships several variants; how do I know
which one I get and how do I pick another?".
Answered by the variants table in
CAPABILITIES.md ## Capabilities and modes.CAPABILITIES.md ## ObservabilityTASKS.md ## test which routes to
doca-pcc-counters.CAPABILITIES.md ## Capabilities and modesdoca_pcc_dev_set_ztr_rttcc_params workflow in
TASKS.md ## use.DOCA_PCC_DEV_STATUS_FAIL or
DOCA_ERROR_* from a doca_pcc_dev_ztr_rttcc_* call
mean and which layer caused it?" — worked example:
"my init callback returns DOCA_PCC_DEV_STATUS_FAIL
on first launch". Answered by the algorithm overlay
on the host-side PCC taxonomy in
CAPABILITIES.md ## Error taxonomyTASKS.md ## debug that escalates
through
doca-pcc and
doca-debug.This skill serves external developers operating a
BlueField-3-class DPU who want to deploy NVIDIA's shipped
reference PCC algorithm on RoCE-v2 traffic, OR who are
evaluating it against a custom algorithm they intend to
write. The reference algorithm is zero-touch by design
— the no-config-required baseline — and the canonical use
case is dropping it onto a port and confirming it shapes
flows correctly under congestion. It is not for NVIDIA
developers contributing to the algorithm itself, nor for
users who want general PCC programming theory (route via
the public DOCA PCC programming guide), nor for users who
only want to inspect PCC counters (route to
doca-pcc-counters).
Language scope. The algorithm ships as a DPA-side
library (pkg-config module doca-pcc-ztr-rttcc-algo)
plus a public header doca_pcc_dev_ztr_rttcc_algo.h that
DPA-side translation units include. The shipped algorithm
binary is the static library
libdoca_pcc_ztr_rttcc_algo_dev.a per the README; the
device-side translation unit that consumes it is C and is
compiled by DPACC. The host-side that drives the PCC
context comes from doca-pcc;
this library does NOT add a host-side surface beyond the
host-side helpers (also shipped as
libdoca_pcc_ztr_rttcc_algo.{a,so} per the README) that
the doca-pcc framework links. Other-language host-side
wrappers around doca-pcc can drive this algorithm through
the same lifecycle described in doca-pcc; the DPA-side
integration always stays C-via-DPACC.
Load this skill when the user is doing hands-on deployment,
tuning, or evaluation of the DOCA-shipped ZTR RTTCC
reference algorithm on a BlueField port carrying RoCE-v2
traffic, in any host language plus the DPA-side translation
unit built by dpacc. Concretely:
doca_pcc_dev_ztr_rttcc_algo); the variants live in
the DPA-side source the user compiles against.doca_pcc_dev_ztr_rttcc_algo.h and the shipped
doca_pcc_dev_set_ztr_rttcc_params).doca-pcc-counters
for the read-only inspection side).Do not load this skill for general DOCA orientation;
for the host-side doca-pcc lifecycle (route to
doca-pcc); for writing a custom
algorithm from scratch (route to
doca-pcc and the public PCC
programming guide via
doca-public-knowledge-map);
for read-only PCC counter inspection (route to
doca-pcc-counters);
or for the default firmware-shipped PCC algorithms that
predate Programmable Congestion Control entirely (no
host-side code, no DPACC compile — that is a firmware-only
path routed via
doca-public-knowledge-map).
This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive algorithm-specific material lives in two companion files:
CAPABILITIES.md — what the shipped ZTR RTTCC
algorithm expresses on this version + this BlueField
generation + this firmware: the public DPA-side API
surface (doca_pcc_dev_ztr_rttcc_init,
doca_pcc_dev_ztr_rttcc_algo,
doca_pcc_dev_set_ztr_rttcc_params,
doca_pcc_dev_ztr_rttcc_get_param_num,
doca_pcc_dev_ztr_rttcc_get_counter_num,
doca_pcc_dev_ztr_rttcc_get_num_of_histograms), the
documented variants (vanilla / path-migration / RX-rate
/ multipath / window-probeless — pick one at
DPA-side compile time), the relationship to the
host-side doca-pcc framework (this is an algorithm
body the framework loads), the relationship to the
doca-pcc-counters tool (which is the canonical
inspection surface), the algorithm's parameter and
counter surface (RTT-based congestion signal,
per-feature parameter blocks), the error taxonomy in
DOCA_PCC_DEV_STATUS_OK / _FAIL, and the safety
policy.TASKS.md — step-by-step workflows for the in-scope
algorithm verbs: install, configure, build,
modify, run, test, debug, use. Plus a
Deferred task verbs block that points out-of-scope
questions at the right next skill.The skill assumes DOCA + the DPACC compiler + the
doca-pcc host-side framework are
already installed; the BlueField is a generation that
exposes the DPA processor (the algorithm runs on the DPA);
the BlueField firmware has the custom-PCC slot enabled
(inherited from
doca-pcc CAPABILITIES.md ## Safety policy);
and the BlueField port the algorithm will modulate has
RoCE-v2 traffic actually flowing on it (the algorithm
modulates existing RDMA / RoCE traffic — without traffic,
there is nothing for it to do).
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:
libdoca_pcc_ztr_rttcc_algo_dev.a (plus the host-side
helpers) installed by the matching DOCA host package
per the README. The agent's job is to route the user to
the installed library and header
(doca_pcc_dev_ztr_rttcc_algo.h) and to prescribe the
in-place edits documented in the README on the
shipped DOCA PCC application source, not to author the
algorithm./opt/mellanox/doca/applications/pcc/ (per the
README). The agent's job is to prescribe the
minimum-diff modifications the README documents and to
walk the user through the rebuild — not to author a
parallel application.doca-public-knowledge-map.
It does not redefine each variant's mathematical
behavior.SKILL.md first to confirm the user's
question is in scope (deployment / tuning / evaluation
of the shipped reference algorithm, not algorithm
design from scratch and not read-only counter
inspection).doca-pcc
framework relationship, the
doca-pcc-counters inspection-side relationship, the
error taxonomy, the observability surface, and the
safety policy, see CAPABILITIES.md.Both companion files cross-link to each other,
doca-pcc for the host-side PCC
lifecycle that loads this algorithm,
doca-pcc-counters
for the read-only counter-inspection side of validating that
the algorithm is modulating traffic,
doca-dpa for the DPA-side
two-side-program model and the DPACC compiler discipline,
doca-version for the
canonical DOCA version-handling rules (with the DPACC
overlay inherited from
doca-dpa and
doca-pcc), and
doca-public-knowledge-map
whenever the right answer is "look it up in the public DOCA
PCC programming guide or the on-disk install layout".
doca-pcc — the host-side PCC
control library. This algorithm is loaded INTO a
doca_pcc context that doca-pcc stands up; the
host-side lifecycle (doca_pcc create / configure /
start / stop / destroy, the algorithm image
doca_pcc_app, the attach-to-port semantics) is owned
by doca-pcc. This skill prescribes only the DPA-side
algorithm integration on top.doca-pcc-counters —
the read-only diagnostic CLI for PCC counters at the
port. The canonical "is the algorithm actually
modulating traffic" check goes through the counter
tool; this skill names what counters the algorithm
emits (CNP / NACK / AI / HAI / decrement / RTT-band
counters per the public header) and routes the
inspection workflow to the tool skill.doca-dpa — the host-side
DPA control library. The algorithm runs on the DPA,
compiled by DPACC; the two-side-program rule and the
DOCA-and-DPACC version-match overlay inherited from
here apply.doca-public-knowledge-map —
the routing table for every public DOCA documentation
source (the DOCA PCC programming guide at
https://docs.nvidia.com/doca/sdk/doca-pcc/index.html;
the DOCA PCC application guide; the DOCA Compatibility
Policy) and the on-disk layout of an installed DOCA
package.doca-setup — env
preparation, install verification, DPACC compiler
install / verification, BlueField firmware
configuration (including the custom-PCC slot enable),
and the I have no install yet path with the public
NGC DOCA container. This skill assumes its
preconditions are satisfied AND that DPACC is installed
at a version that matches DOCA AND that the firmware-
level custom-PCC slot is enabled.doca-version —
canonical DOCA version-handling rules. This skill's
## Version compatibility cross-links the four-way
match rule plus the DOCA-and-DPACC overlay inherited
from doca-pcc.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. This skill layers
algorithm-specific overlays on top of the universal
build, modify-a-shipped-sample, and Core lifecycle
patterns.doca-debug — cross-cutting
debug ladder. Algorithm-specific debug (the algorithm
loaded but counters do not move; the algorithm fails to
initialize; the algorithm modulates traffic too
aggressively / too gently for the workload) overlays on
top of that ladder.doca-hardware-safety —
cross-cutting hardware-safety meta-policy. Because the
algorithm modulates production RoCE-v2 flows on a
BlueField port, the meta-policy's pre-flight inventory,
replica-first, and rollback rules apply via this
skill's ## Safety policy overlay.© 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-pcc-ztr-rttcc-algo of NVIDIA/skills.
Open the folder on GitHubat commit 14a98ae
Doca Pcc Ztr Rttcc Algo 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 Pcc Ztr Rttcc Algo this skillNVIDIA/skills | 3.6k | — | ~4.8k | Automated safety check: Pass | Apache-2.0 | |
| Monitor CInrwl/nx | 29k | 6 repos | ~4.7k | Automated safety check: Pass | MIT | |
| Terraform and OpenTofu Guideagentscope-ai/QwenPaw | 36k | 6 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Vercel Optimize Auditvercel-labs/agent-skills | 32k | 8 repos | ~4.3k | Automated safety check: Pass | None | |
| Analyze GitHub Action Logswithastro/astro | 63k | 1 repos | ~1.3k | Automated safety check: Pass | Custom licence | |
| Openclaw Live Updateropenclaw/openclaw | 392k | — | ~3.7k | Automated safety check: Pass | MIT |
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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 deployment, tuning, or evaluation of the DOCA-shipped Zero-Touch RoCE RTT-based Congestion Control (ZTR RTTCC) reference algorithm on a…. Doca Pcc Ztr Rttcc Algo 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 deployment, tuning, or evaluation of the DOCA-shipped Zero-Touch RoCE RTT-based Congestion Control (ZTR RTTCC) reference algorithm on a BlueField-3 DPA — wiring docapccdevztrrttccalgo into the shipped DOCA PCC sample, picking a variant (vanilla / PM / RX-rate / multipath / window-probeless) at DPACC build time, tuning host-set parameters, or diagnosing DOCAPCCDEVSTATUSFAIL from the algorithm.
Doca Pcc Ztr Rttcc Algo fits situations like: the user is doing hands-on deployment; picking a variant (vanilla / PM / RX-rate / multipath / window-probeless) at DPACC build time; tuning host-set parameters; diagnosing DOCAPCCDEVSTATUSFAIL from the algorithm.
Run `npx skills add NVIDIA/skills --skill doca-pcc-ztr-rttcc-algo -a claude-code`. Or copy the skill folder (skills/doca-pcc-ztr-rttcc-algo in NVIDIA/skills) into .claude/skills/doca-pcc-ztr-rttcc-algo in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill doca-pcc-ztr-rttcc-algo -a codex`. Or copy the skill folder (skills/doca-pcc-ztr-rttcc-algo in NVIDIA/skills) into .agents/skills/doca-pcc-ztr-rttcc-algo 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-pcc-ztr-rttcc-algo -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-pcc-ztr-rttcc-algo, .gemini/skills/doca-pcc-ztr-rttcc-algo, .github/skills/doca-pcc-ztr-rttcc-algo and .opencode/skills/doca-pcc-ztr-rttcc-algo in your project.
SKILL.md names no scripts, command-line tools or credentials: Doca Pcc Ztr Rttcc Algo 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-3 DPU exposing the DPA processor, the firmware custom-PCC slot enabled, a matched-version DPACC compiler, and live RoCE-v2 traffic on the attached port. Reads `pkg-config doca-pcc-ztr-rttcc-algo` and inspects /opt/mellanox/doca/{lib,include,applications/pcc}. .
SKILL.md names 1 domain. As links in the text: docs.nvidia.com. 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 Pcc Ztr Rttcc Algo 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 4.8k tokens (SKILL.md is roughly 19k 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 Pcc Ztr Rttcc Algo: Monitor CI (nrwl/nx, 29k stars), Terraform and OpenTofu Guide (agentscope-ai/QwenPaw, 36k stars), Vercel Optimize Audit (vercel-labs/agent-skills, 32k stars) and Analyze GitHub Action Logs (withastro/astro, 63k 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 3,555 GitHub stars. The repository holds 390 skills in this directory. The repository was last updated on October 9, 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.