[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-nvidia-doca-eth":3,"mdc-93lc7a-key":31,"related-repo-nvidia-doca-eth":1378,"related-org-nvidia-doca-eth":1484},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":20,"repoUrl":21,"updatedAt":22,"license":23,"forks":24,"topics":25,"repo":26,"sourceUrl":29,"mdContent":30},"doca-eth","manage DOCA Ethernet packet queues","Use this skill for hands-on DOCA Ethernet packet-queue work on a BlueField DPU or ConnectX NIC — bringing up a `doca_eth_rxq` or `doca_eth_txq` on a port \u002F representor \u002F SF, picking among the four `enum doca_eth_rxq_type` values (`_REGULAR` \u002F `_CYCLIC` \u002F `_MANAGED_MEMPOOL` \u002F `_SHARED_MEMPOOL`), sizing burst or scatter-gather length against the `_cap_*` queries, submitting `doca_eth_txq_task_send` \u002F `_lso_send` (carrying packet `doca_buf`s — no `doca_eth_frame` struct exists), or debugging DOCA_ERROR_* from an Ethernet call. Trigger on implicit phrasings: \"my RX queue is up but no packets arrive\", \"send-task returns AGAIN at line rate\", \"which queue type for fixed-MTU ingress\", \"device open fails without sudo\", or \"is L3 checksum offload available here\". Refuse and route elsewhere for installing DOCA, flow-rule \u002F steering programming, host↔DPU control messaging, or RDMA data movement.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},"nvidia","NVIDIA","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fnvidia.png",[12,16,17],{"name":13,"slug":14,"type":15},"Networking","networking","tag",{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},"Engineering","engineering",2473,"https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fskills","2026-07-20T06:24:17.721288","Apache-2.0",281,[],{"repoUrl":21,"stars":20,"forks":24,"topics":27,"description":28},[],"AI agent skills published by NVIDIA","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fskills\u002Ftree\u002FHEAD\u002Fskills\u002Fdoca-eth","---\nlicense: Apache-2.0\nname: doca-eth\ndescription: >\n  Use this skill for hands-on DOCA Ethernet packet-queue work\n  on a BlueField DPU or ConnectX NIC — bringing up a\n  `doca_eth_rxq` or `doca_eth_txq` on a port \u002F representor \u002F\n  SF, picking among the four `enum doca_eth_rxq_type` values\n  (`_REGULAR` \u002F `_CYCLIC` \u002F `_MANAGED_MEMPOOL` \u002F\n  `_SHARED_MEMPOOL`), sizing burst or scatter-gather length\n  against the `_cap_*` queries, submitting\n  `doca_eth_txq_task_send` \u002F `_lso_send` (carrying packet\n  `doca_buf`s — no `doca_eth_frame` struct exists), or\n  debugging DOCA_ERROR_* from an Ethernet call. Trigger on\n  implicit phrasings: \"my RX queue is up but no packets\n  arrive\", \"send-task returns AGAIN at line rate\", \"which\n  queue type for fixed-MTU ingress\", \"device open fails\n  without sudo\", or \"is L3 checksum offload available here\".\n  Refuse and route elsewhere for installing DOCA,\n  flow-rule \u002F steering programming, host↔DPU control\n  messaging, or RDMA data movement.\nmetadata:\n  kind: library\ncompatibility: >\n  Requires DOCA SDK installed at \u002Fopt\u002Fmellanox\u002Fdoca on Linux\n  (Ubuntu 22.04\u002F24.04 or RHEL\u002FSLES) with a BlueField DPU or\n  ConnectX NIC attached. Reads the user's local install via\n  `pkg-config doca-eth` and inspects\n  \u002Fopt\u002Fmellanox\u002Fdoca\u002F{lib,include,samples,applications}.\n---\n\n# DOCA Ethernet\n\n**Where to start:** This skill assumes DOCA is already installed and\nthe user is doing **hands-on packet-queue work** on a host or\nBlueField with DOCA. Open [`TASKS.md`](TASKS.md) if the user wants\nto *do* something (configure \u002F build \u002F modify \u002F run \u002F test \u002F\ndebug); open [`CAPABILITIES.md`](CAPABILITIES.md) when the question\nis *what can a DOCA Ethernet queue express* on this version. If\nthe user has not installed DOCA yet, route to\n[`doca-setup`](..\u002F..\u002Fdoca-setup\u002FSKILL.md) first. If the user is\nasking *\"how do I get packets to land on my RX queue at all\"*, the\nanswer lives in [`doca-flow`](..\u002Fdoca-flow\u002FSKILL.md) — DOCA\nEthernet is the *queue* surface; DOCA Flow is the *steering*\nsurface, and they are independent libraries.\n\n## Example questions this skill answers well\n\nThe CLASSES of DOCA Ethernet questions this skill is built to\nanswer, each with one worked example. The agent should treat the\n*class* as the load-bearing piece — the worked example is a single\ninstance.\n\n- **\"How do I bring up an RX and TX queue on a representor or\n  physical port?\"** — worked example: *\"set up a `doca_eth_rxq`\n  plus a `doca_eth_txq` on a single BlueField representor for\n  first-run testing\"*. Answered by the queue-pair lifecycle in\n  [`TASKS.md ## configure`](TASKS.md#configure) +\n  [`CAPABILITIES.md ## Capabilities and modes`](CAPABILITIES.md#capabilities-and-modes)\n  RX \u002F TX object table.\n- **\"Which RX type fits my data shape — regular, cyclic, or\n  managed-recv?\"** — worked example: *\"line-rate ingress with\n  fixed-size frames into a pre-allocated buffer ring\"*. Answered\n  by the RX-type taxonomy in\n  [`CAPABILITIES.md ## Capabilities and modes`](CAPABILITIES.md#capabilities-and-modes)\n  + the capability-query rule (`doca_eth_rxq_cap_is_type_supported`\n  against a `doca_devinfo`) in\n  [`TASKS.md ## configure`](TASKS.md#configure).\n- **\"How do I send a packet from user code through `doca_eth_txq`?\"**\n  — worked example: *\"allocate a packet `doca_buf`, attach the\n  payload, submit one send-task, wait for the completion event\"*.\n  Answered by the TX submission shape in\n  [`CAPABILITIES.md ## Capabilities and modes`](CAPABILITIES.md#capabilities-and-modes)\n  + the property-set workflow in\n  [`TASKS.md ## modify`](TASKS.md#modify).\n- **\"My queue is up but no packets arrive — why?\"** — worked\n  example: *\"`doca_eth_rxq` started cleanly but the recv callback\n  never fires\"*. Answered by the steering-dependency rule in\n  [`CAPABILITIES.md ## Safety policy`](CAPABILITIES.md#safety-policy)\n  + the env-prep checklist in\n  [`TASKS.md ## configure`](TASKS.md#configure) step 1, which\n  routes the steering side to\n  [`doca-flow`](..\u002Fdoca-flow\u002FSKILL.md) and the\n  promiscuous-mode side to\n  [`doca-setup`](..\u002F..\u002Fdoca-setup\u002FSKILL.md).\n- **\"Is this Ethernet capability available on my device + my\n  installed DOCA?\"** — worked example: *\"does this device\n  advertise L3 checksum offload\"*. Answered by the\n  capability-query rule (`doca_eth_txq_cap_is_l3_chksum_offload_supported`\n  against a `doca_devinfo`) in\n  [`CAPABILITIES.md ## Capabilities and modes`](CAPABILITIES.md#capabilities-and-modes)\n  + the version-and-device overlay in\n  [`CAPABILITIES.md ## Version compatibility`](CAPABILITIES.md#version-compatibility).\n- **\"What does this `DOCA_ERROR_*` from an Ethernet call mean and\n  which layer caused it?\"** — worked example: *\"`DOCA_ERROR_AGAIN`\n  on `doca_task_submit` for an `eth_txq` send-task at high rate\"*.\n  Answered by the Ethernet overlay on the cross-library taxonomy\n  in\n  [`CAPABILITIES.md ## Error taxonomy`](CAPABILITIES.md#error-taxonomy)\n  + the layered ladder in\n  [`TASKS.md ## debug`](TASKS.md#debug) that escalates to\n  [`doca-debug`](..\u002F..\u002Fdoca-debug\u002FSKILL.md).\n\n## Audience\n\nThis skill serves **external developers building applications that\nconsume the DOCA Ethernet library** — i.e., users whose code calls\n`doca_eth_rxq_*` \u002F `doca_eth_txq_*` (directly in C\u002FC++, or through\nFFI\u002Fbindings from another language) to do line-rate packet I\u002FO on\nphysical ports, representors, or SFs of a BlueField or ConnectX\ndevice. It is *not* for NVIDIA developers contributing to DOCA\nEthernet itself.\n\n**Language scope.** DOCA Ethernet ships as a C library with\n`pkg-config` module name `doca-eth`. The shipped samples are\nwritten in C. C and C++ consumers are the canonical case; the\nworked examples in `TASKS.md` assume that path. Other-language\nconsumers (Rust, Go, Python, …) consume the same `*.so` through\nFFI or language-specific bindings; the skill's contribution in\nthat case is to keep the queue-object split, lifecycle,\ncapability-discovery, permission, RX-type taxonomy, and\nerror-taxonomy guidance language-neutral, and to route the agent\nto the public C ABI as the authoritative surface that any wrapper\nwill eventually call.\n\n## When to load this skill\n\nLoad this skill when the user is doing hands-on DOCA Ethernet\nwork, in any language. Concretely:\n\n- Initializing a `doca_eth_rxq` on a `doca_dev` opened against a\n  physical port, a representor, or an SF — choosing among the\n  regular \u002F cyclic \u002F managed-recv RX types based on data shape\n  before `doca_ctx_start()`.\n- Initializing a `doca_eth_txq` on the same or a different\n  `doca_dev` and posting send-tasks against packet `doca_buf`s\n  payload buffers.\n- Reading or setting Ethernet queue properties via\n  `doca_eth_rxq_set_*` \u002F `doca_eth_txq_set_*` and querying device\n  capability via `doca_eth_rxq_cap_*` \u002F `doca_eth_txq_cap_*`\n  (max burst size, RX-type support, max scatter-gather length,\n  checksum-offload presence).\n- Confirming the port is up and that traffic is actually steered\n  to the chosen RX queue — either via DOCA Flow rules (the\n  canonical path) or via kernel-side promiscuous mode (the\n  expedient first-run path).\n- Wiring an Ethernet queue to a higher-level data plane: GPU\n  packet processing via DOCA GPUNetIO, custom user-space\n  forwarding agents, or telemetry mirrors that snap a copy of\n  every packet.\n- Debugging a `DOCA_ERROR_*` returned from an Ethernet call\n  (lifecycle vs. permission vs. capability vs. send-queue-full\n  vs. driver-below) and the per-queue progress engine events.\n- Designing or extending non-C bindings (Rust, Go, Python, …)\n  that wrap the DOCA Ethernet C ABI — for the lifecycle, queue\n  split, RX-type, capability, and permission rules the wrapper\n  must honor.\n\nDo **not** load this skill for general DOCA orientation, install\nof DOCA itself, flow-rule programming (use\n[`doca-flow`](..\u002Fdoca-flow\u002FSKILL.md)), host ↔ DPU control\nmessaging (use [`doca-comch`](..\u002Fdoca-comch\u002FSKILL.md)), or\nRDMA data movement (use [`doca-rdma`](..\u002Fdoca-rdma\u002FSKILL.md)).\nFor DOCA documentation orientation, use\n[`doca-public-knowledge-map`](..\u002F..\u002Fdoca-public-knowledge-map\u002FSKILL.md).\n\n## What this skill provides\n\nThis is a **thin loader**. The body keeps only the orientation\nneeded to pick the right next file. The substantive Ethernet-\nspecific material lives in two companion files:\n\n- `CAPABILITIES.md` — what a DOCA Ethernet queue can express on\n  this version: the RX \u002F TX object split, the RX-type taxonomy\n  (regular \u002F cyclic \u002F managed-recv), the send-task \u002F frame\n  submission surface, the capability-query surface\n  (`doca_eth_rxq_cap_*` \u002F `doca_eth_txq_cap_*`), the Ethernet\n  error taxonomy (mapped onto the cross-library `DOCA_ERROR_*`\n  set), the observability surface (per-queue progress engine\n  events, capability snapshots), and the safety policy that\n  gates the steering \u002F permission \u002F port-state preconditions.\n- `TASKS.md` — step-by-step workflows for the six in-scope\n  Ethernet verbs: `configure`, `build`, `modify`, `run`,\n  `test`, `debug`. Plus a `Deferred task verbs` block that\n  points out-of-scope questions at the right next skill, and a\n  `Command appendix` of the recurring commands the agent\n  reaches for.\n\nThe skill assumes a host or BlueField where DOCA is already\ninstalled at the standard location and the user has the\nprivileges their public install profile expects (typically sudo\nor `mlnx`-group membership to open a `doca_dev` against a port).\nIt does not cover installing DOCA — that path goes through\n[`doca-setup`](..\u002F..\u002Fdoca-setup\u002FSKILL.md).\n\n## What this skill deliberately does not ship\n\nThis skill is **agent guidance**, not a samples or templates\nbundle. To keep the boundary clean, it deliberately does not\ncontain — and pull requests should not add:\n\n- **Pre-written DOCA Ethernet application source code, in any\n  language.** The verified Ethernet source code is the shipped C\n  samples at `\u002Fopt\u002Fmellanox\u002Fdoca\u002Fsamples\u002Fdoca_eth\u002F\u003Cname>\u002F`. The\n  agent's job is to route the user to those files and prescribe\n  a minimum-diff modification on them via the universal\n  modify-a-sample workflow in\n  [`doca-programming-guide`](..\u002F..\u002Fdoca-programming-guide\u002FSKILL.md),\n  layered with the Ethernet-specific overrides in\n  [`TASKS.md ## modify`](TASKS.md#modify).\n- **Standalone build manifests** (`meson.build`,\n  `CMakeLists.txt`, `Cargo.toml`, …) parked inside the skill.\n  The agent constructs the build manifest *in the user's project\n  directory* against the user's installed DOCA, where\n  `pkg-config --modversion doca-eth` is the source of truth.\n- **A `samples\u002F`, `bindings\u002F`, or `reference\u002F` subtree** of any\n  kind. A mock or incomplete artifact in this skill's tree, even\n  one labeled \"reference\", is misleading: users will read it as\n  buildable.\n\n## Loading order\n\n1. Read this `SKILL.md` first to confirm the user's question is\n   in scope.\n2. **For the Ethernet capability matrix, RX-type taxonomy, send\n   surface, capability-query rules, error taxonomy,\n   observability, and safety policy, see\n   [CAPABILITIES.md](CAPABILITIES.md).**\n3. **For step-by-step workflows — configure, build, modify, run,\n   test, debug — see [TASKS.md](TASKS.md).**\n\nBoth companion files cross-link to each other,\n[`doca-version`](..\u002F..\u002Fdoca-version\u002FSKILL.md) for the canonical\nversion-handling rules,\n[`doca-flow`](..\u002Fdoca-flow\u002FSKILL.md) for the steering side\nthat the RX queue depends on, and\n[`doca-public-knowledge-map`](..\u002F..\u002Fdoca-public-knowledge-map\u002FSKILL.md)\nwhenever the right answer is \"look it up in the public docs or\nthe installed package layout\" rather than \"Ethernet-specific\nguidance\".\n\n## Related skills\n\n- [`doca-public-knowledge-map`](..\u002F..\u002Fdoca-public-knowledge-map\u002FSKILL.md) —\n  the routing table for every public DOCA documentation source\n  and the on-disk layout of an installed DOCA package. The\n  Ethernet URL slug is `DOCA-Ethernet`.\n- [`doca-setup`](..\u002F..\u002Fdoca-setup\u002FSKILL.md) — env preparation,\n  install verification, port-state checks (`devlink dev show`,\n  `ip link`), permission and group-membership requirements for\n  opening a `doca_dev`. This skill assumes its preconditions\n  are satisfied.\n- [`doca-version`](..\u002F..\u002Fdoca-version\u002FSKILL.md) — canonical\n  DOCA version-handling rules. This skill's `## Version\n  compatibility` cross-links the four-way match rule and adds\n  only the Ethernet-specific overlay (RX-type availability\n  windows, checksum-offload device-conditional support).\n- [`doca-structured-tools-contract`](..\u002F..\u002Fdoca-structured-tools-contract\u002FSKILL.md) —\n  the bundle's structured-tools precedence rule (detect \u002F prefer\n  \u002F fall back \u002F report). The Command appendix in\n  [TASKS.md](TASKS.md) honors this contract.\n- [`doca-programming-guide`](..\u002F..\u002Fdoca-programming-guide\u002FSKILL.md) —\n  general DOCA programming patterns shared by every library:\n  the canonical `pkg-config` + meson build pattern, the\n  universal modify-a-shipped-sample first-app workflow, the\n  universal lifecycle, the cross-library `DOCA_ERROR_*`\n  taxonomy, and the program-side debug order. This skill layers\n  Ethernet specifics on top.\n- [`doca-flow`](..\u002Fdoca-flow\u002FSKILL.md) — the steering surface\n  that decides which packets land on which `doca_eth_rxq`. DOCA\n  Ethernet does *not* program steering itself; an empty RX queue\n  almost always means a missing or wrong Flow rule, not an\n  Ethernet bug.\n- [`doca-debug`](..\u002F..\u002Fdoca-debug\u002FSKILL.md) — the cross-cutting\n  debug ladder (install \u002F version \u002F build \u002F link \u002F runtime \u002F\n  program \u002F driver). Ethernet-specific debug (RX-type\n  mismatches, send-queue-full retries, steering-empty-queue\n  symptoms) overlays on top of that ladder.\n",{"data":32,"body":36},{"license":23,"name":4,"description":6,"metadata":33,"compatibility":35},{"kind":34},"library","Requires DOCA SDK installed at \u002Fopt\u002Fmellanox\u002Fdoca on Linux (Ubuntu 22.04\u002F24.04 or RHEL\u002FSLES) with a BlueField DPU or ConnectX NIC attached. Reads the user's local install via `pkg-config doca-eth` and inspects \u002Fopt\u002Fmellanox\u002Fdoca\u002F{lib,include,samples,applications}.\n",{"type":37,"children":38},"root",[39,48,151,158,170,564,570,605,645,651,656,773,829,835,847,951,980,986,998,1120,1126,1169,1206,1212],{"type":40,"tag":41,"props":42,"children":44},"element","h1",{"id":43},"doca-ethernet",[45],{"type":46,"value":47},"text","DOCA Ethernet",{"type":40,"tag":49,"props":50,"children":51},"p",{},[52,58,60,65,67,78,80,86,88,97,99,104,106,116,118,123,125,135,137,142,144,149],{"type":40,"tag":53,"props":54,"children":55},"strong",{},[56],{"type":46,"value":57},"Where to start:",{"type":46,"value":59}," This skill assumes DOCA is already installed and\nthe user is doing ",{"type":40,"tag":53,"props":61,"children":62},{},[63],{"type":46,"value":64},"hands-on packet-queue work",{"type":46,"value":66}," on a host or\nBlueField with DOCA. Open ",{"type":40,"tag":68,"props":69,"children":71},"a",{"href":70},"TASKS.md",[72],{"type":40,"tag":73,"props":74,"children":76},"code",{"className":75},[],[77],{"type":46,"value":70},{"type":46,"value":79}," if the user wants\nto ",{"type":40,"tag":81,"props":82,"children":83},"em",{},[84],{"type":46,"value":85},"do",{"type":46,"value":87}," something (configure \u002F build \u002F modify \u002F run \u002F test \u002F\ndebug); open ",{"type":40,"tag":68,"props":89,"children":91},{"href":90},"CAPABILITIES.md",[92],{"type":40,"tag":73,"props":93,"children":95},{"className":94},[],[96],{"type":46,"value":90},{"type":46,"value":98}," when the question\nis ",{"type":40,"tag":81,"props":100,"children":101},{},[102],{"type":46,"value":103},"what can a DOCA Ethernet queue express",{"type":46,"value":105}," on this version. If\nthe user has not installed DOCA yet, route to\n",{"type":40,"tag":68,"props":107,"children":109},{"href":108},"..\u002F..\u002Fdoca-setup\u002FSKILL.md",[110],{"type":40,"tag":73,"props":111,"children":113},{"className":112},[],[114],{"type":46,"value":115},"doca-setup",{"type":46,"value":117}," first. If the user is\nasking ",{"type":40,"tag":81,"props":119,"children":120},{},[121],{"type":46,"value":122},"\"how do I get packets to land on my RX queue at all\"",{"type":46,"value":124},", the\nanswer lives in ",{"type":40,"tag":68,"props":126,"children":128},{"href":127},"..\u002Fdoca-flow\u002FSKILL.md",[129],{"type":40,"tag":73,"props":130,"children":132},{"className":131},[],[133],{"type":46,"value":134},"doca-flow",{"type":46,"value":136}," — DOCA\nEthernet is the ",{"type":40,"tag":81,"props":138,"children":139},{},[140],{"type":46,"value":141},"queue",{"type":46,"value":143}," surface; DOCA Flow is the ",{"type":40,"tag":81,"props":145,"children":146},{},[147],{"type":46,"value":148},"steering",{"type":46,"value":150},"\nsurface, and they are independent libraries.",{"type":40,"tag":152,"props":153,"children":155},"h2",{"id":154},"example-questions-this-skill-answers-well",[156],{"type":46,"value":157},"Example questions this skill answers well",{"type":40,"tag":49,"props":159,"children":160},{},[161,163,168],{"type":46,"value":162},"The CLASSES of DOCA Ethernet questions this skill is built to\nanswer, each with one worked example. The agent should treat the\n",{"type":40,"tag":81,"props":164,"children":165},{},[166],{"type":46,"value":167},"class",{"type":46,"value":169}," as the load-bearing piece — the worked example is a single\ninstance.",{"type":40,"tag":171,"props":172,"children":173},"ul",{},[174,232,290,349,420,476],{"type":40,"tag":175,"props":176,"children":177},"li",{},[178,183,185,206,208,218,220,230],{"type":40,"tag":53,"props":179,"children":180},{},[181],{"type":46,"value":182},"\"How do I bring up an RX and TX queue on a representor or\nphysical port?\"",{"type":46,"value":184}," — worked example: ",{"type":40,"tag":81,"props":186,"children":187},{},[188,190,196,198,204],{"type":46,"value":189},"\"set up a ",{"type":40,"tag":73,"props":191,"children":193},{"className":192},[],[194],{"type":46,"value":195},"doca_eth_rxq",{"type":46,"value":197},"\nplus a ",{"type":40,"tag":73,"props":199,"children":201},{"className":200},[],[202],{"type":46,"value":203},"doca_eth_txq",{"type":46,"value":205}," on a single BlueField representor for\nfirst-run testing\"",{"type":46,"value":207},". Answered by the queue-pair lifecycle in\n",{"type":40,"tag":68,"props":209,"children":211},{"href":210},"TASKS.md#configure",[212],{"type":40,"tag":73,"props":213,"children":215},{"className":214},[],[216],{"type":46,"value":217},"TASKS.md ## configure",{"type":46,"value":219}," +\n",{"type":40,"tag":68,"props":221,"children":223},{"href":222},"CAPABILITIES.md#capabilities-and-modes",[224],{"type":40,"tag":73,"props":225,"children":227},{"className":226},[],[228],{"type":46,"value":229},"CAPABILITIES.md ## Capabilities and modes",{"type":46,"value":231},"\nRX \u002F TX object table.",{"type":40,"tag":175,"props":233,"children":234},{},[235,240,241,246,248,256],{"type":40,"tag":53,"props":236,"children":237},{},[238],{"type":46,"value":239},"\"Which RX type fits my data shape — regular, cyclic, or\nmanaged-recv?\"",{"type":46,"value":184},{"type":40,"tag":81,"props":242,"children":243},{},[244],{"type":46,"value":245},"\"line-rate ingress with\nfixed-size frames into a pre-allocated buffer ring\"",{"type":46,"value":247},". 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This skill assumes its preconditions\nare satisfied.",{"type":40,"tag":175,"props":1271,"children":1272},{},[1273,1281,1283,1289],{"type":40,"tag":68,"props":1274,"children":1275},{"href":1176},[1276],{"type":40,"tag":73,"props":1277,"children":1279},{"className":1278},[],[1280],{"type":46,"value":1183},{"type":46,"value":1282}," — canonical\nDOCA version-handling rules. 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The Command appendix in\n",{"type":40,"tag":68,"props":1307,"children":1308},{"href":70},[1309],{"type":46,"value":70},{"type":46,"value":1311}," honors this contract.",{"type":40,"tag":175,"props":1313,"children":1314},{},[1315,1323,1325,1330,1332,1337],{"type":40,"tag":68,"props":1316,"children":1317},{"href":1021},[1318],{"type":40,"tag":73,"props":1319,"children":1321},{"className":1320},[],[1322],{"type":46,"value":1028},{"type":46,"value":1324}," —\ngeneral DOCA programming patterns shared by every library:\nthe canonical ",{"type":40,"tag":73,"props":1326,"children":1328},{"className":1327},[],[1329],{"type":46,"value":620},{"type":46,"value":1331}," + meson build pattern, the\nuniversal modify-a-shipped-sample first-app workflow, the\nuniversal lifecycle, the cross-library ",{"type":40,"tag":73,"props":1333,"children":1335},{"className":1334},[],[1336],{"type":46,"value":489},{"type":46,"value":1338},"\ntaxonomy, and the program-side debug order. 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Ethernet-specific debug (RX-type\nmismatches, send-queue-full retries, steering-empty-queue\nsymptoms) overlays on top of that ladder.",{"items":1379,"total":1483},[1380,1397,1411,1425,1437,1454,1469],{"slug":1381,"name":1381,"fn":1382,"description":1383,"org":1384,"tags":1385,"stars":20,"repoUrl":21,"updatedAt":1396},"accelerated-computing-cudf","accelerate data processing with cuDF","Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV\u002FParquet I\u002FO, nullable semantics, and multi-GPU DataFrame workloads.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1386,1389,1392,1393],{"name":1387,"slug":1388,"type":15},"Data Analysis","data-analysis",{"name":1390,"slug":1391,"type":15},"Data Engineering","data-engineering",{"name":9,"slug":8,"type":15},{"name":1394,"slug":1395,"type":15},"Performance","performance","2026-07-14T05:28:43.176466",{"slug":1398,"name":1398,"fn":1399,"description":1400,"org":1401,"tags":1402,"stars":20,"repoUrl":21,"updatedAt":1410},"aiq-deploy","deploy and manage NVIDIA AI-Q infrastructure","Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1403,1406,1409],{"name":1404,"slug":1405,"type":15},"Deployment","deployment",{"name":1407,"slug":1408,"type":15},"Infrastructure","infrastructure",{"name":9,"slug":8,"type":15},"2026-07-14T05:29:06.667109",{"slug":1412,"name":1412,"fn":1413,"description":1414,"org":1415,"tags":1416,"stars":20,"repoUrl":21,"updatedAt":1424},"aiq-research","conduct deep research with AI-Q","Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1417,1420,1421],{"name":1418,"slug":1419,"type":15},"Agents","agents",{"name":9,"slug":8,"type":15},{"name":1422,"slug":1423,"type":15},"Research","research","2026-07-14T05:28:06.816956",{"slug":1426,"name":1426,"fn":1427,"description":1428,"org":1429,"tags":1430,"stars":20,"repoUrl":21,"updatedAt":1436},"amc-run-sample-calibration","run AMC sample dataset calibration","Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. 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For RTSP\u002Flive streams, use amc-run-rtsp-calibration instead.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1443,1446,1449,1450],{"name":1444,"slug":1445,"type":15},"Automation","automation",{"name":1447,"slug":1448,"type":15},"Imaging","imaging",{"name":9,"slug":8,"type":15},{"name":1451,"slug":1452,"type":15},"Video","video","2026-07-17T05:28:53.905004",{"slug":1455,"name":1455,"fn":1456,"description":1457,"org":1458,"tags":1459,"stars":20,"repoUrl":21,"updatedAt":1468},"amc-setup-calibration-stack","deploy AutoMagicCalib microservice with Docker","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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1460,1461,1464,1465],{"name":1404,"slug":1405,"type":15},{"name":1462,"slug":1463,"type":15},"Docker","docker",{"name":9,"slug":8,"type":15},{"name":1466,"slug":1467,"type":15},"Operations","operations","2026-07-17T05:28:56.913999",{"slug":1470,"name":1470,"fn":1471,"description":1472,"org":1473,"tags":1474,"stars":20,"repoUrl":21,"updatedAt":1482},"cudaq-guide","develop quantum applications with CUDA-Q","CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1475,1476,1479],{"name":9,"slug":8,"type":15},{"name":1477,"slug":1478,"type":15},"Quantum Computing","quantum-computing",{"name":1480,"slug":1481,"type":15},"Simulation","simulation","2026-07-14T05:26:58.898253",305,{"items":1485,"total":1636},[1486,1504,1520,1531,1543,1557,1570,1584,1595,1604,1618,1627],{"slug":1487,"name":1487,"fn":1488,"description":1489,"org":1490,"tags":1491,"stars":1501,"repoUrl":1502,"updatedAt":1503},"nemoclaw-user-guide","retrieve NemoClaw documentation and configuration","Guides human users' AI agents to the NemoClaw docs MCP server and canonical Fern documentation in Markdown form. 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Covers the two pin sites (GitHub CI in `docker\u002F.ngc_version.dev` and GitLab CI in `.gitlab\u002Fstages\u002F01.build.yml`), the post-bump CI loop (re-run functional tests, refresh golden values, mark broken tests), and the gotchas that bit PRs",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1526,1529],{"name":1527,"slug":1528,"type":15},"CI\u002FCD","ci-cd",{"name":1404,"slug":1405,"type":15},"2026-07-14T05:25:59.97109",{"slug":1532,"name":1532,"fn":1533,"description":1534,"org":1535,"tags":1536,"stars":1517,"repoUrl":1518,"updatedAt":1542},"mcore-cicd","manage CI\u002FCD pipelines for Megatron-LM","CI\u002FCD reference for Megatron-LM. Covers CI pipeline structure, PR scope labels, triggering internal GitLab CI (which force-pushes the current branch to a pull-request\u002FBRANCH ref — always dry-run and verify the destination first; never run against shared or protected branches), and CI failure investigation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1537,1538,1539],{"name":1527,"slug":1528,"type":15},{"name":1404,"slug":1405,"type":15},{"name":1540,"slug":1541,"type":15},"GitHub","github","2026-07-27T06:06:12.278222",{"slug":1544,"name":1544,"fn":1545,"description":1546,"org":1547,"tags":1548,"stars":1517,"repoUrl":1518,"updatedAt":1556},"mcore-create-issue","investigate CI failures and create issues","Investigate a failing GitHub Actions run or job and create a GitHub issue for the failure.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1549,1552,1553],{"name":1550,"slug":1551,"type":15},"Debugging","debugging",{"name":1540,"slug":1541,"type":15},{"name":1554,"slug":1555,"type":15},"Triage","triage","2026-07-14T05:25:57.442089",{"slug":1558,"name":1558,"fn":1559,"description":1560,"org":1561,"tags":1562,"stars":1517,"repoUrl":1518,"updatedAt":1569},"mcore-linting-and-formatting","lint and format Megatron-LM code","Linting and formatting for Megatron-LM. Covers running autoformat.sh, tools (ruff, black, isort, pylint, mypy), and code style rules.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1563,1566],{"name":1564,"slug":1565,"type":15},"Best Practices","best-practices",{"name":1567,"slug":1568,"type":15},"Code Analysis","code-analysis","2026-07-14T05:25:56.18433",{"slug":1571,"name":1571,"fn":1572,"description":1573,"org":1574,"tags":1575,"stars":1517,"repoUrl":1518,"updatedAt":1583},"mcore-migrate-gpt-to-hybrid","migrate Megatron-LM models to HybridModel","Migration guide for moving Megatron Core GPTModel checkpoints, model providers, training commands, and layer mappings to HybridModel.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1576,1579,1582],{"name":1577,"slug":1578,"type":15},"Machine Learning","machine-learning",{"name":1580,"slug":1581,"type":15},"Migration","migration",{"name":9,"slug":8,"type":15},"2026-07-17T06:07:11.777011",{"slug":1585,"name":1585,"fn":1586,"description":1587,"org":1588,"tags":1589,"stars":1517,"repoUrl":1518,"updatedAt":1594},"mcore-onboard-gb200-1node-tests","onboard functional tests for GB200","Onboard 1-node GitHub MR functional tests for GB200 from existing mr-scoped 2-node tests.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1590,1593],{"name":1591,"slug":1592,"type":15},"QA","qa",{"name":1434,"slug":1435,"type":15},"2026-07-14T05:25:53.673039",{"slug":1596,"name":1596,"fn":1597,"description":1598,"org":1599,"tags":1600,"stars":1517,"repoUrl":1518,"updatedAt":1603},"mcore-run-on-slurm","launch distributed training jobs on SLURM","How to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules across hardware and parallelism modes, container conventions, monitoring, and per-rank failure diagnosis.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1601,1602],{"name":1404,"slug":1405,"type":15},{"name":1407,"slug":1408,"type":15},"2026-07-14T05:25:49.362534",{"slug":1605,"name":1605,"fn":1606,"description":1607,"org":1608,"tags":1609,"stars":1517,"repoUrl":1518,"updatedAt":1617},"mcore-split-pr","split pull requests to reduce review load","Split a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1610,1613,1614],{"name":1611,"slug":1612,"type":15},"Code Review","code-review",{"name":1540,"slug":1541,"type":15},{"name":1615,"slug":1616,"type":15},"Pull Requests","pull-requests","2026-07-14T05:26:01.226578",{"slug":1619,"name":1619,"fn":1620,"description":1621,"org":1622,"tags":1623,"stars":1517,"repoUrl":1518,"updatedAt":1626},"mcore-testing","run and manage Megatron-LM tests","Test system for Megatron-LM. Covers test layout, recipe YAML structure, adding and running unit and functional tests, golden values, marker filters, and CI parity.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1624,1625],{"name":1591,"slug":1592,"type":15},{"name":1434,"slug":1435,"type":15},"2026-07-14T05:25:54.928983",{"slug":1628,"name":1628,"fn":1629,"description":1630,"org":1631,"tags":1632,"stars":1517,"repoUrl":1518,"updatedAt":1635},"nightly-sync","manage nightly main-to-dev sync workflows","Domain knowledge for the nightly main-to-dev sync workflow. Covers merge strategy, CI architecture, failure investigation, and known issues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":9},[1633,1634],{"name":1444,"slug":1445,"type":15},{"name":1527,"slug":1528,"type":15},"2026-07-30T05:29:03.275638",496]