trtllm-moe-develop

trtllm-moe-develop is an MLOps & model serving skill for AI agents, published by NVIDIA in the TensorRT-LLM repository on GitHub. Skillspace rates trtllm-moe-develop D (63/100) and it passed the safety scan; the rating is based on static analysis only.

Review, design, and refactor TensorRT-LLM PyTorch MoE code for architecture fit, clean code, maintainability, and testability. Always use for any modification, review, refactor, or design planning that touches MoE modules, including tensorrt_llm/_torch/modules/fused_moe, ConfigurableMoE, MoE backends, MoEScheduler/moe_scheduler.py, forward execution/chunking, communication strategies, EPLB, quantization/weight handling, routing, factories, MoE docs, or MoE tests. Also use when the user asks whether a MoE design follows the current architecture or whether a MoE refactor is reasonable.

Grade
D
Quality
63 / 100
Safety
Passed
GitHub stars
14,127

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

Our review

Architecture
75 / 100
Maturity
Packaged: licensed, with a version or references
Security scan
Low-risk patterns
License
Not declared. Check the repository before reusing it.
Adoption
Adopted by 0 other repositories, in 0 collections
Scope
Repo-internal: written for the repository it lives in. Edits TensorRT-LLM's own MoE modules and coding guidelines

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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