edge-fm-cuda-kernel-optimizer

edge-fm-cuda-kernel-optimizer is a Runtime diagnostics & profiling skill for AI agents, published by windog-labs in the edge-fm-x repository on GitHub. Skillspace rates edge-fm-cuda-kernel-optimizer B (81/100) and it passed the safety scan; the rating is based on static analysis only.

NCU-guided CUDA/CUTLASS kernel optimization workflow for edge-fm-x, including short standalone/repo-in-place tuning and long Humanize + KernelPilot loops. Use when optimizing kernels under src/, tuning standalone CUDA/CUTLASS reproductions, or when the user asks to speed up an Edge-FM CUDA kernel and mentions Nsight Compute, Nsight Systems, NCU, benchmark plateaus, Humanize, KernelPilot, long-running kernel search, source provenance, ledgers, CUTLASS, latency regressions, or iterative optimization.

Grade
B
Quality
81 / 100
Safety
Passed
GitHub stars
30

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.

View source on GitHubwindog-labs/edge-fm-x

Our review

Architecture
100 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
Apache-2.0
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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