Skip to main content

review-op-bench-coverage

Review a CV-CUDA operator's BENCHMARK coverage — drivers, layout axis, baselines, the basic-tier floor, row counts, and coverage statistics. Use when asked whether an operator's benchmarks/baselines are complete or to find/fill bench gaps.

Source facts

Repository
CVCUDA/CV-CUDA
Last source activity
August 11, 2026 at 21:59
Detected SKILL.md language
English
Stars
2,729
Forks
264

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

Showing SKILL.md

SKILL.md
Source instructions · Read-only preview
name
review-op-bench-coverage
description
Review a CV-CUDA operator's BENCHMARK coverage — drivers, layout axis, baselines, the basic-tier floor, row counts, and coverage statistics. Use when asked whether an operator's benchmarks/baselines are complete or to find/fill bench gaps.
[//]: # "SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved." [//]: # "SPDX-License-Identifier: Apache-2.0" # Review Op — bench coverage Thin entry point. Run `python3 tools/review_op.py <Operator> --domain bench` (add `--run` for the GPU-run-dependent checks) and interpret per the **bench** section (BEN-*) of `.agents/guidance/REVIEW_OP_GUIDELINES.md`: structural rules + the hard basic-tier minimum floor (BEN-14) + advisory coverage statistics and `RECOMMENDATION`s. Resolve `MANUAL` items at the cited locations. When fixing (`--fix`), add the layout axis and required native/reference layout configs, then recompute row counts - a missing-SKU **baseline gap is reported "requires CI" and never fabricated** — and re-run to confirm. Findings-first.
View on GitHub