optimize-op-preflight

Check whether a CV-CUDA operator is READY to optimize (correctness + bench coverage + captured baseline + profiling) per .agents/guidance/OPTIMIZATION_GUIDELINES.md. Use before starting an optimization campaign to confirm the readiness gate is clean.

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Repositório: CVCUDA/CV-CUDA
Última atividade na origem: 11 de agosto de 2026 às 21:59
Idioma detectado do SKILL.md: inglês
Estrelas: 2.729
Forks: 264

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Follow https://skillsmp.com/skill-install/prompt.md to install only the Agent Skill at https://github.com/CVCUDA/CV-CUDA/tree/main/.agents/skills/optimize-op-preflight.

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npx skills add https://github.com/CVCUDA/CV-CUDA --skill optimize-op-preflight

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SKILL.md

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name: optimize-op-preflight
description: Check whether a CV-CUDA operator is READY to optimize (correctness + bench coverage + captured baseline + profiling) per .agents/guidance/OPTIMIZATION_GUIDELINES.md. Use before starting an optimization campaign to confirm the readiness gate is clean.

[//]: # "SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved." [//]: # "SPDX-License-Identifier: Apache-2.0" # Optimize Op — preflight Thin entry point. Run `python3 tools/optimize_op.py <Op> --phase preflight` and interpret per the tool's readiness (PRE-*) findings against `.agents/guidance/OPTIMIZATION_GUIDELINES.md`: correctness/regression coverage and benchmark coverage (reused from `review_op.py` test+bench), a captured baseline, and profiling tools. Any `GAP` means the operator is not ready — add the missing coverage **first**, in a separate non-`perf:` commit, before starting the optimization. Resolve `MANUAL` items at the cited locations. Findings-first.

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make-op

Add a new CV-CUDA operator end-to-end per .agents/guidance/MAKE_OP_GUIDELINES.md, with a deterministically-enforced definition-of-done. Use when asked to create/add a new operator, scaffold one, or verify that a new operator is complete (approved spec, wired scaffold, bit-exact regression tests across the declared support matrix, required layout parity, complement negatives, docs + relnote, benched dtypes, tests that run and pass, optimization-ready).

2026-09-16

refactor-op

Find and safely apply per-operator refactoring / redundancy-reduction opportunities in a CV-CUDA operator (near-duplicate Tensor/VarShape kernels, reinvented shared utilities, dead code). Use when asked to reduce code duplication, de-duplicate or unify an operator's kernels/bindings, remove dead code, or verify a refactor changed nothing observable. Produces a deterministic findings-first report; the apply path is gated by a strict bit-exact / feature-set / test-coverage parity check.

2026-09-16

make-op-scaffold

Scaffold a new CV-CUDA operator — a complete, wired, building skeleton — and delegate the implementation to a human or another AI. Use when asked to set up / stub out a new operator without implementing it, or to bootstrap one for someone else to finish. Supports --bare (skip the spec when the definition itself is delegated).

2026-08-11

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optimize-op-preflight

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