nvrx-attr

от nvidia

Orchestration layer over nvidia_resiliency_ext attribution modules. Provides log-analysis, fr-analysis, and a Megatron-LM-oriented fault-injection feedback…

npx skills add https://github.com/nvidia/nvidia-resiliency-ext --skill nvrx-attr

Attribution Skills

High-level orchestration layer over the nvidia_resiliency_ext.attribution modules. Each subdirectory is a self-contained skill with its own SKILL.md and helper scripts.

Skills

DirectoryPurposeEntry point
log-analysis/Analyze SLURM job logs for failure root-cause and restart decisionsNVRxLogAnalyzer (nvrx_logsage.py)
fr-analysis/Analyze NCCL flight-recorder dumps for collective-hang root-causeCollectiveAnalyzer (fr_attribution.py)
fault-injection-loop/Run a batched SLURM fault-injection feedback loop and score attribution accuracyprepare_node_alloc.sh / watch_and_analyze.sh

How skills relate to the library

src/nvidia_resiliency_ext/
├── attribution/
│   ├── log_analyzer/nvrx_logsage.py      ← log-analysis implementation
│   ├── trace_analyzer/fr_attribution.py  ← fr-analysis implementation
│   ├── analyzer/engine.py                ← combined orchestration entry point
│   └── combined_log_fr/                  ← optional log + FR fusion
└── skills/
    └── nvrx-attr/                        ← this skill bundle
        ├── log-analysis/
        ├── fr-analysis/
        └── fault-injection-loop/

The Analyzer (analyzer/engine.py) is the recommended entry point when you need request coalescing, result caching, or the combined LOG_AND_TRACE pipeline. Use the individual skills when you want to run one analysis type directly without the full coalescing stack.

Common prerequisites

  • LLM_API_KEY environment variable, LLM_API_KEY_FILE, or ~/.llm_api_key
  • langchain-openai installed
  • logsage package installed (required by log_analysis)
  • Package installed: pip install nvidia-resiliency-ext or pip install -e . from repo root
  • The fault-injection loop has only been validated with Megatron-LM training scripts

Fault-Loop Local Setup

Before using fault-injection-loop/, create the local config file from the tracked template and fill in your site-specific values:

cp scripts/user.env.example scripts/user.env

The feedback-loop scripts require src/nvidia_resiliency_ext/skills/nvrx-attr/scripts/user.env to exist at runtime. Keep user.env local and untracked.

Больше skills от nvidia

compileiq-debug
nvidia
Use when something is wrong: Search() hangs, all evaluations return INVALID_SCORE, scores aren't improving, every config returns the same number, ptxas errors…
official
create-github-pr
nvidia
Create GitHub pull requests using the gh CLI. Use when the user wants to create a new PR, submit code for review, or open a pull request. Trigger keywords -…
official
diagnose-perf
nvidia
First-responder performance triage for Isaac Sim and Isaac Lab. Identifies bottleneck category (GPU-bound, CPU-bound, VRAM, loading) using nvidia-smi and…
official
eagle3-review-logs
nvidia
Review EAGLE3 pipeline experiment logs from the launcher's experiments/ directory. Summarizes pass/fail status for all 4 tasks, diagnoses failures with root…
official
nemoclaw-maintainer-cross-issue-sweep
nvidia
Сканирует другие открытые задачи, чтобы найти те, которые данный PR может исправить или случайно сломать. Выводит возможности смежных исправлений и риски противоречий с указанием файла:строки…
official
karpathy-guidelines
nvidia
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes,…
official
fhir-basics
nvidia
Обучает агентов работе с API FHIR R4, доступным ресурсам, запросам с параметрами поиска и корректному разбору всех форматов ответов…
official
underdeclared-agent
nvidia
A helpful assistant agent
official