git clone --depth 1 https://github.com/NVIDIA/skills /tmp/doca-public-knowledge-map && cp -r /tmp/doca-public-knowledge-map/skills/doca-public-knowledge-map ~/.claude/skills/doca-public-knowledge-mapSKILL.md
# 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. ## 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 th
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Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
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Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
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