# 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.

- Skill: `cvcuda/review-op-bench-coverage` (Agent Skill)
- Install (CLI): `npx skillmds@latest add cvcuda/review-op-bench-coverage`
- Raw SKILL.md: https://api.skillmd.com/api/skills/cvcuda/review-op-bench-coverage/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: cvcuda (https://skillmd.com/u/cvcuda)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/cvcuda/review-op-bench-coverage

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[//]: # "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.