git clone --depth 1 https://github.com/NVIDIA/skills /tmp/doca-debug && cp -r /tmp/doca-debug/skills/doca-debug ~/.claude/skills/doca-debugSKILL.md
# DOCA debug **Where to start:** This skill is the canonical layered-ladder reference both [`doca-setup ## debug`](../doca-setup/TASKS.md#debug) and [`doca-programming-guide ## debug`](../doca-programming-guide/TASKS.md#debug) escalate to. If the symptom does not fit cleanly in env-class or program-class, start at [`TASKS.md ## debug`](TASKS.md#debug) — the full layered ladder lives there. ## Example questions this skill answers well The CLASSES of debug questions this skill is built to answer, each with one worked example. - **"My DOCA build / link / runtime / program failed — which layer is it?"** — worked example: *"`ld` says `undefined reference to doca_flow_init` — which layer?"* Answered by the canonical layered ladder in [`TASKS.md ## debug`](TASKS.md#debug) (layer 4 = Link). - **"How do I turn up verbosity for any DOCA library or tool?"** — worked example: *"My DOCA Flow program is silent — where do I get more log output?"* Answered by the trace-flavor / log-level surface in [`CAPABILITIES.md ## Observability`](CAPABILITIES.md#observability) + the run-with-verbosity workflow in [`TASKS.md ## run`](TASKS.md#run). - **"How do I capture state for a forum question or bug report?"** — worked example: *"I'd like to file a forum question with reproducible context — what should I include?"* Answered by the capture-a-reproducible-state workflow in [`TASKS.md ## test`](TASKS.md#test). - **"What does this DOCA tool's output mean / which tool answers this?"** — worked example: *"`doca_caps` returned nothing for RDMA — does that mean unsupported?"* Answered by the tool-vs-capability decision tree in [`CAPABILITIES.md ## Capabilities and modes`](CAPABILITIES.md#capabilities-and-modes) + cross-link to [doca-caps](../tools/doca-caps/SKILL.md). - **"I'm debugging inside the NGC container — what's observable?"** — worked example: *"`hugepages` is empty inside the container; is that a real problem or a container thing?"* Answered by the container-specific debug constraints in [`CAPABILITIES.md ## Safety policy`](CAPABILITIES.md#safety-policy) + [`TASKS.md ## debug`](TASKS.md#debug) layer 5 (Runtime). - **"Where do I ask for help with this?"** — worked example: *"Where is the customer-facing DOCA forum and what should the post contain?"* Answered by the Developer-Forum routing rule in [`TASKS.md ## debug`](TASKS.md#debug) plus [doca-public-knowledge-map](../doca-public-knowledge-map/SKILL.md). If the symptom is purely env-class, route to [`doca-setup ## debug`](../doca-setup/TASKS.md#debug); if purely program-class, route to [`doca-programming-guide ## debug`](../doca-programming-guide/TASKS.md#debug). This skill is the cross-cutting layer both call into. ## When to load this skill Load this skill when the user is debugging anything DOCA-related — a build that won't compile, a link step that can't resolve a `doca_*` symbol, a runtime call that returns `DOCA_ERROR_*`, a packet that does not appear on the wire, a service that won't start, or a tool that returns no useful output. Concretely: - The user reports a symptom and needs to find the layer that caused it (install / version / build / link / runtime / program). - The user asks "how do I get more logs?" or "how do I turn up the verbosity?" for any DOCA library or tool. - The user wants to capture state for a forum question or an internal bug report (the bundle does not own the internal-bug-report channel; it routes to the public DOCA Developer Forum). - The user is reading a stack trace, a `valgrind` output, or a core dump from a DOCA program and wants to know where to look first. - The user is debugging *inside* the NGC DOCA container and needs to know what is and is not observable from inside it. Do **not** load this skill for: - *"What is `DOCA_ERROR_BAD_STATE`?", "what error codes does DOCA return?"* — that is the cross-library *error taxonomy*, owned by [`doca-programming-guide CAPABILITIES.md ## Error taxonomy`](../doca-programming-guide/CAPABILITIES.md#error-taxonomy). This skill consumes that taxonomy; it does not redefine it. - *"My `pkg-config` cannot find `doca-flow`", "hugepages are not mounted", "my representor isn't visible"* — those are env-class symptoms, owned by [`doca-setup ## debug`](../doca-setup/TASKS.md#debug). This skill is the canonical pointer that env-class debug ladder redirects to once the symptom escalates beyond install / version / build prerequisites. - *Library-specific debugging* (Flow pipe trace, RDMA queue-pair state, Comch channel statistics) — those live in the matching library skill (e.g. [`doca-flow ## debug`](../libs/doca-flow/TASKS.md#debug)). This skill provides the cross-cutting debug ladder; library skills layer their library-specific debug surface on top of it. ## What this skill provides This is a **thin loader**. The body keeps only the orientation needed to pick the right next file. The substantive debug material lives in two companion files: - [CAPABILITIES.md](CAPABILITIES.md) — what *kinds of debug surface* DOCA exposes: the layered debug model (install / version / build / link / runtime / program), the read-only-first stance, version-availability of debug tools (e.g. `doca_caps` since DOCA 2.6.0), the cross-library error taxonomy (cross-link only — owned by `doca-programming-guide`), the observability primitives DOCA emits (`stderr` logs, `--sdk-log-level`, the `doca-<lib>-trace` build flavor, library counters), and the safety constraints on debug actions (read-only first, don't mutate install tree mid-investigation). - [TASKS.md](TASKS.md) — the actual debug workflows: `## configure` (set up env for high-verbosity debug), `## test` (capture a reproducible state), `## debug` (the canonical layered ladder, the universal entry point that every library `## debug` redirects to), and the *Where to ask for help* routing (NVIDIA DOCA Developer Forum). Three other anchors (`build`, `modify`, `run`) exist for lint compliance and route to [
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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'.
Calibrate a new dataset from pre-recorded video files via the AutoMagicCalib REST API. Use when user has local MP4s and says 'calibrate my videos', 'run AMC on these videos', or similar. For RTSP/live streams, use amc-run-rtsp-calibration instead.
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.