doca-public-knowledge-map
Use this skill to locate authoritative NVIDIA DOCA information without the source tree: the docs.nvidia.com page for a library/service/tool, which DOCA…
Skill by NVIDIA <doca@nvidia.com>
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/nvidia-doca-public-knowledge-map
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: documents, backend
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/doca-public-knowledge-map
What's inside
- Skill name
doca-public-knowledge-map- Description
- Use this skill to locate authoritative NVIDIA DOCA information without the source tree: the docs.nvidia.com page for a library/service/tool, which DOCA libraries are installed and at what version, a sample on disk or GitHub, a path under /opt/mellanox/doca, or a 404'd/renamed doc URL. Activate on implicit phrasing only when the conversation already names DOCA, BlueField, ConnectX, or /opt/mellanox. Do not activate for generic 'which version is installed' or 'where is the sample' questions with none of that context. Refuse and route elsewhere for hands-on programming, env prep, API tutorials, or hardware/firmware mutation — those belong to doca-programming-guide, doca-setup, the per-library skills, and doca-hardware-safety.
- License
- Apache-2.0 AND CC-BY-4.0
- Compatibility
- No DOCA install required to read this skill (it is an overlay loaded against any DOCA artifact skill); the validation steps within this skill require a live DOCA install at /opt/mellanox/doca.
- Metadata
- kind: knowledge · author: NVIDIA <doca@nvidia.com> · doca_version: 3.5
- Instructions
- 229 lines in SKILL.md · view on GitHub
Files (11)
- BENCHMARK.md
- SKILL.md
- evals.json · evals/
- external-dpu.md · references/
- external-fabric.md · references/
- libraries.md · references/
- map.md · references/
- services.md · references/
- tools.md · references/
- skill-card.md
- skill.oms.sig
SKILL.md (first lines)
# DOCA Public Knowledge Map **Where to start:** Reach for this skill whenever the question is "where does the authoritative answer live?" — a docs page, the on-disk install layout, a sample, or an NGC catalog entry. Read [`## Public documentation entry points`](#public-documentation-entry-points) first; then jump to the routing-table section that matches the user's intent. **How to use this skill.** Read this file, then search the companion file for the `## <name>` heading the question needs and read that whole section. Answer completely from it, quoting only its symbols and commands. Do not browse docs; use the entry points in `doca-public-knowledge-map`. Give environment checks as commands for the user's DOCA host. For out-of-scope requests, name the skill that owns them and stop. ## When to load this skill Load this skill whenever the user asks anything about NVIDIA DOCA where the agent needs to **locate authoritative information** without access to the DOCA source tree. That includes **documentation-routing questions** about installing DOCA, building a sample, learning a DOCA library (Flow, DPA, Comm Channel, GPUNetIO, …), debugging an error, finding an API or error reference, finding a sample, release notes, or the developer forum. This skill locates the authoritative answer; hands-on installation, building, tutorials, and debugging route to the workflow-owning skills named in the frontmatter and [`## Related skills`](#related-skills). This skill is intentionally a **routing table**, not a tutorial. Pick the entry that matches the user's intent, fetch the URL or inspect the local install path, and only then answer. ## First-contact discovery — the four questions to ask before any drill-down When a user opens with an open-ended orientation question (*"I'm new with DOCA, how do I start?"*, *"can you guide me?"*, *"what's the easiest way to try DOCA?"*), the agent does **not** have enough information yet to pick a path. Asking these four questions before drilling avoids wasted recommendations that the user cannot actually execute on their setup. Ask them as a single short message; do not interrogate one-at-a-time. | Question | Why it matters | What it routes | | --- | --- | --- | | 1. **What OS are you on?** macOS, Windows, Linux laptop, cloud VM, lab Linux box, BlueField OS itself? | DOCA installs natively only on supported Linux distributions; macOS / Windows users cannot install it at all. | Picks between the four DOCA acquisition paths in `doca-setup ## no-install` (`doca-setup/TASKS.md#no-install`). macOS / Windows / no-Linux → Path 0 (NGC container). Supported Linux → Path A or B per the Installation Guide. | | 2. **What hardware do you have?** No NVIDIA hardware, ConnectX SmartNIC, BlueField as a SmartNIC in a host, BlueField as a standalone DPU, not sure? | Real-traffic runtime needs a real NIC; build / read / learn does not. The user's hardware decides which DOCA libraries are even relevant. | Picks the runtime story (container is build-only without hardware). Filters which libraries make sense to learn (Flow needs a real port to do anything visible; Comch needs a host ↔ DPU pair). | | 3. **What's your goal?** Just exploring, building a small first app on a specific library (Flow / RDMA / Comch / Telemetry / GPUNetIO / DPA / …), running an existing reference application, operating a service (DMS / DTS / BlueMan / Firefly), or something else? | The bundle's first-app workflow (`doca-programming-guide ## modify`) starts from a **shipped C sample** and edits down. The right sample depends on the library the user is targeting. | Picks which library skill (if any) to load next. If the user does not yet know which library — that itself is a routing answer (see the *Library- and module-specific guides* table above and let the user pick). | | 4. **Which language do you plan to write the program in?** C / C++, Rust, Go, Python, other? | DOCA's public surface is a C ABI. Non-C consumers go through FFI / language bindings (`doca-programming-guide CAPABILITIES.md ## Capabilities and modes` and the per-library skill). The C samples are the reference even when the user's language is not C. | Picks whether the agent's first-app guidance is *direct C build* or *FFI / bindings against the C ABI*. Does **not** change which sample the agent points at first. | The four-question gate applies when an open-ended orientation, install, build, or run recommendation depends on the user's environment. For that class, **never recommend a specific install path, container tag, or runnable sample without first having the answers to questions 1–3** (question 4 is needed for the first-app workflow but not for orientation itself). Pure documentation lookups — a URL, API reference, sample location, version reference, or stale-link recovery — skip this gate and route directly. If the user cannot or will not answer a required question, state which environment-dependent recommendation cannot be made, give only the safe version-agnostic umbrella documentation route, and do not guess the missing value. Volunteering specific commands before this is the single most common failure mode for DOCA orientation. If the user has already volunteered some of the information in their first message, mark those questions answered and only ask the rest. Do not re-ask what the user has already told you. ## Topic to "where to look first" routing table When the user asks something, route as follows: | User intent | First place to look | | --- | --- | | "How do I install DOCA?" | Installation Guide + Downloads page (Public documentation entry points). | | "How do I start with DOCA — what's the very first thing?" | Developer Quick Start Guide *if* the user has BlueField + host hardware; otherwise `doca-setup ## no-install` (`doca-setup/TASKS.md#no-install`) Path 0 (NGC container). Use the four questions in [*First-contact discovery*](#first-contact-discovery--the-four-questions-to-ask-before-any-drill-down) to pick. | | "Do I need a BlueField? A SmartNIC? Or just DOCA-Host?" | Overview page (`doca-overview/index.html`) plus the Installation Guide's *DOCA installation profiles* section. The bundle does not pick the hardware for the user — these two pages do. | | "Which package gives me library X?" | Installation Guide section on package matrix; then verify on the user's system with `pkg-config --list-all`. | | "Show me a sample that uses library X." | `/opt/mellanox/doca/samples/doca_<X>/` if installed; otherwise the per-library guide on `docs.nvidia.com/doca/sdk/` (each library guide documents the samples shipped with it). | | "How do I build a DOCA sample?" | Library guide + the sample's own `meson.build` inside `/opt/mellanox/doca/samples/...`. | | "What is the API for X?" | Library guide; confirm by inspecting headers under `$(pkg-config --variable=includedir doca-common)` (commonly `/opt/mellanox/doca/include/` on DOCA 3.3+; `/opt/mellanox/doca/infrastructure/include/` on legacy / split-profile installs). | | "Why does my build fail with `pkg-config` not finding `doca-...`?" | "Layout of an installed DOCA package" (`PKG_CONFIG_PATH`), then load `doca-setup/SKILL.md` for environment preparation and debugging; do not silently mutate the environment. | | "What is the latest version / what changed?" | Release Notes. | | "Is there a newer DOCA — should I upgrade / downgrade / roll back?" | `doca-upgrade/SKILL.md` for the detect → report → ASK → guided-upgrade discipline (never auto-upgrade); Release Notes for what the target release contains. | | "Is the component I depend on being sunset / deprecated?" | Release Notes (lifecycle / deprecation notices), reached via the `doca-upgrade/SKILL.md` sunset-awareness check; do not assert deprecation from memory. | | "What does the DOCA version number mean? Is LTS still supported?" | Compatibility Policy (Public documentation entry points table). | | "How do I run DOCA on Kubernetes / provision a DPU?" | DOCA Platform Framework on GitHub. | | "I have a behavior I cannot explain." | Release Notes (known issues) first; then the DOCA Developer Forum. Never go to the forum first. | | Any intent not matched above | Start at the DOCA SDK index and the Libraries / Services / Tools umbrella page in `references/map.md` (public documentation entry points). If the authoritative route remains unresolved, say so and use the Developer Forum; do not invent a URL or component name. | ## What this skill deliberately does not cover This file is intentionally a **map**, not a tutorial. It does not contain: - DOCA library tutorials (those live in the per-library guides). - API reference (lives in headers and the per-library guides). - Build-system deep-dives (lives in the Installation Guide and the sample `meson.build` files). - Performance tuning, driver-level setup, OFED interaction (lives in the Installation Guide and library-specific guides). When the agent needs those, it should fetch the matching public document or read the matching installed file. As more focused skills are added, they should appear in bundle `SKILLS.md` and link back here for the "where to look" lookups. ## Related skills For env preparation — install verification, build environment (`pkg-config`, headers, hugepages, devlink), env-class debugging, and the *I have no install yet* path with the public NGC DOCA container on the catalog Tags page as the universal Stage-1 fallback for any user on macOS, Windows, or Linux without DOCA — load `doca-setup/SKILL.md`. That skill stops at *"the install is healthy and the env is ready"*. For general DOCA programming patterns shared across every library — the canonical `pkg-config doca-<library>` build pattern (C/C++ direct or non-C via FFI), the universal *derive a custom first app from a shipped sample* workflow, the universal lifecycle (`cfg-create → init → start → use → stop → destroy`), the cross-library `DOCA_ERROR_*` taxonomy, and the program-side debug order — load `doca-programming-guide/SKILL.md`. Each library skill extends its `## modify` (first-app derivation) with
From NVIDIA/skills, Apache-2.0 AND CC-BY-4.0.
More from NVIDIA/skills
- 0.846score
nemo-fabric-integrate
NVIDIA Corporation and Affiliates
Use this skill when integrating NVIDIA NeMo Fabric into a consumer application, service, evaluation harness, or platform through the typed Python SDK —…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
jetson-video-pipeline
Vinit Bansal <vinitkumarb@nvidia.com>
Use when planning, executing, and independently validating Jetson Video Codec SDK or PyNvVideoCodec encode/decode, transcode, segmentation, container decode…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
nvflare-convert-pytorch
NVIDIA FLARE Team <federatedlearning@nvidia.com>
Convert existing plain or manual PyTorch training code into an NVFLARE federated job using Client API model exchange, local validation, and job export; use…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
nemo-relay-get-started
NVIDIA Corporation and Affiliates
Use this skill when first-time NeMo Relay users want help selecting and following an appropriate quick-start guide or verifying their first working integration.
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
jetson-video-recipe
Vinit Bansal <vinitkumarb@nvidia.com>
Use when turning a Jetson encoder use case into one surface-neutral recipe with native Video Codec SDK and PyNvVideoCodec projections.
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
nvidia-broadcast
NVIDIA Broadcast Team <broadcast-skills-dev@nvidia.com>
Use when controlling NVIDIA Broadcast through MCP to apply effects, process local media, select devices, or change camera resolution, or when Broadcast is…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
jetson-video-setup
Vinit Bansal <vinitkumarb@nvidia.com>
Use when installing, repairing, reusing, inspecting, or verifying readiness of the native NVIDIA Video Codec SDK or PyNvVideoCodec on Jetson, including the…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
nvflare-diagnose-job
NVIDIA FLARE Team <federatedlearning@nvidia.com>
Use when the user asks why a reported NVFLARE job failure signal occurred: the job failed, stalled, timed out, lost clients, ended with EXECUTION_EXCEPTION…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
nvflare-convert-lightning
NVIDIA FLARE Team <federatedlearning@nvidia.com>
Convert existing PyTorch Lightning training code into an NVFLARE federated job using the Lightning Client API patch, local validation, and job export; use…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
nemo-relay-install
NVIDIA Corporation and Affiliates
Use this skill when choosing or running NeMo Relay installation for an agent runtime, application language, framework integration, or plugin bundle, or…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
nvflare-fed-stats
NVIDIA FLARE Team <federatedlearning@nvidia.com>
Compute federated statistics over tabular data (count, sum, mean, stddev, var, histogram, quantile, noise-protected min/max) and image data (count…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.846score
jetson-video-capability
Vinit Bansal <vinitkumarb@nvidia.com>
Use when Jetson codec, profile, chroma, bit-depth, dimension, engine-count, or operational support must be reconciled from live APIs, authenticated NVIDIA…
SkillAFreshness: A★ 3.7KClaude Code +9
Signals
- Stars
- 3,718
- Forks
- 457
- Open issues
- 8
- Last commit (this folder)
- Oct 22, 2026 (6 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0 AND CC-BY-4.0
- Repository
- github.com/NVIDIA/skills
- Website
- docs.nvidia.com/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from NVIDIA <doca@nvidia.com>
- 0.790score
doca-bf4-deployment
NVIDIA <doca@nvidia.com>
WARNING: guides IRREVERSIBLE BlueField-4 hardware operations (PLDM firmware burns, ISO reflashes, power cycles, BMC factory resets); every mutating step is…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.790score
doca-container-deployment
NVIDIA <doca@nvidia.com>
Running an in-bundle DOCA service as a container on a BlueField (Argus, DMS, Firefly, or UROM service): kubelet standalone watching a static-pod manifests…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.790score
doca-bf3-deployment
NVIDIA <doca@nvidia.com>
Use this skill for BlueField-3 (BF3) day-1 platform bring-up via the classic RShim/BFB path: pushing a BlueField bundle (BFB) to the DPU over RShim with…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.790score
doca-bare-metal-deployment
NVIDIA <doca@nvidia.com>
Running a DOCA-linked binary directly on the hardware, with no container or kubelet: on host x86 with a BlueField NIC over PCIe, or bare-metal on BlueField Arm.
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.790score
doca-collectx-deployment
NVIDIA <doca@nvidia.com>
Use this skill to deploy and operate a CollectX (clx) based DOCA telemetry collector on a host or BlueField — wiring providers / counters into the collector…
SkillAFreshness: A★ 3.7KClaude Code +9 - 0.790score
doca-verbs
NVIDIA <doca@nvidia.com>
Raw verbs inside DOCA Core (doca-verbs): direct control of QP, CQ, PD, SRQ and address-handle objects through doca_verbs_context and doca_verbs_qp_create /…
SkillAFreshness: A★ 3.7KClaude Code +9
Cite this page
doca-public-knowledge-map skill. Agent Mart. https://agentmart.dev/skills/nvidia-doca-public-knowledge-map (last updated 2026-10-24)