How do I install the Techtide Nvidia AI Networking Fabric Review skill?

Run npx skillmds@latest add techtideohio/techtide-nvidia-ai-networking-fabric-review in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Techtide Nvidia AI Networking Fabric Review free to use?

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Who published Techtide Nvidia AI Networking Fabric Review?

TechTideOhio (@techtideohio) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Techtide Nvidia AI Networking Fabric Review by techtideohio

Name: Techtide Nvidia AI Networking Fabric Review
Author: TechTideOhio

Techtide Nvidia AI Networking Fabric Review

Use this skill when reviewing NVIDIA AI networking fabrics - Spectrum-X Ethernet or InfiniBand topology, NCCL collective tuning, RoCEv2 lossless DCQCN/PFC config, adaptive routing, congestion control, and east-west isolation between training jobs. Trigger when the user asks whether the fabric is non-blocking, whether NCCL chooses the right transport, whether PFC/ECN is configured correctly, or whether the deployment meets NCP-AIN expectations.

TechTideOhio Updated Sep 17, 2026

File contents

NVIDIA AI Networking Fabric Review

Purpose

Review NVIDIA AI fabric configuration against the NCP-AIN body of knowledge: rail-optimized topology, NCCL collective communication tuning (NCCL_TOPO, NCCL_IB_HCA, NCCL_NET_GDR_LEVEL), RoCEv2 lossless DCQCN/PFC, InfiniBand subnet manager and partitioning, adaptive routing, and tenant/job east-west isolation.

Lean operating rules

Prefer live evidence (ibstat, ibdiagnet, nccl-tests all_reduce_perf baselines, ethtool -S, switch QoS counters) when the active client exposes it; otherwise fall back to NVIDIA Spectrum-X / Quantum InfiniBand documentation and sanitized topology diagrams.
Separate confirmed facts from inference. If NCCL transport selection, PFC posture, or partition keys were not directly queried, say so.
Treat a non-rail-optimized topology presented as rail-optimized as a critical finding - collective performance claims are wrong.
Treat RoCEv2 deployed without PFC + ECN (DCQCN) as a high finding - lossless behavior is not provided; goodput collapses under congestion.
Treat default NCCL settings on multi-rail systems as a medium finding when published baselines are missing - transport selection is unverified.
Treat shared partition keys (PKey 0x7FFF / default) across tenants on a multi-tenant InfiniBand fabric as a high finding - east-west isolation is absent.
Treat absence of nccl-tests baselines stored alongside the cluster spec as a medium finding - regressions cannot be detected.
Treat subnet manager running on a single switch with no failover as a high finding for production fabrics.

Response minimum

Return, at minimum:

the scoped target (fabric type, generation, scale) and evidence level,
topology and rail posture,
NCCL transport and tuning posture,
lossless/PFC/ECN posture (RoCEv2) or PKey/partition posture (InfiniBand),
tenant isolation posture,
safe next actions and assumptions or blockers.

---name: techtide-nvidia-ai-networking-fabric-reviewdescription: Use this skill when reviewing NVIDIA AI networking fabrics - Spectrum-X Ethernet or InfiniBand topology, NCCL collective tuning, RoCEv2 lossless DCQCN/PFC config, adaptive routing, congestion control, and east-west isolation between training jobs. Trigger when the user asks whether the fabric is non-blocking, whether NCCL chooses the right transport, whether PFC/ECN is configured correctly, or whether the deployment meets NCP-AIN expectations.---# NVIDIA AI Networking Fabric Review## PurposeReview NVIDIA AI fabric configuration against the NCP-AIN body of knowledge: rail-optimized topology, NCCL collective communication tuning (NCCL_TOPO, NCCL_IB_HCA, NCCL_NET_GDR_LEVEL), RoCEv2 lossless DCQCN/PFC, InfiniBand subnet manager and partitioning, adaptive routing, and tenant/job east-west isolation.## Lean operating rules- Prefer live evidence (`ibstat`, `ibdiagnet`, `nccl-tests` `all_reduce_perf` baselines, `ethtool -S`, switch QoS counters) when the active client exposes it; otherwise fall back to NVIDIA Spectrum-X / Quantum InfiniBand documentation and sanitized topology diagrams.- Separate confirmed facts from inference. If NCCL transport selection, PFC posture, or partition keys were not directly queried, say so.- Treat a non-rail-optimized topology presented as rail-optimized as a critical finding - collective performance claims are wrong.- Treat RoCEv2 deployed without PFC + ECN (DCQCN) as a high finding - lossless behavior is not provided; goodput collapses under congestion.- Treat default NCCL settings on multi-rail systems as a medium finding when published baselines are missing - transport selection is unverified.- Treat shared partition keys (PKey 0x7FFF / default) across tenants on a multi-tenant InfiniBand fabric as a high finding - east-west isolation is absent.- Treat absence of `nccl-tests` baselines stored alongside the cluster spec as a medium finding - regressions cannot be detected.- Treat subnet manager running on a single switch with no failover as a high finding for production fabrics.## Response minimumReturn, at minimum:- the scoped target (fabric type, generation, scale) and evidence level,- topology and rail posture,- NCCL transport and tuning posture,- lossless/PFC/ECN posture (RoCEv2) or PKey/partition posture (InfiniBand),- tenant isolation posture,- safe next actions and assumptions or blockers.

Frequently asked questions