mflux-testing — apple-silicon mflux-testing, community, apple-silicon, ide skills, diffusers, huggingface, qwen-image, seedvr2, transformers, z-image

v1.0.0

关于此技能

非常适合需要使用pytest和Makefile目标进行高级图像测试和验证的机器学习代理。 Run tests in mflux (fast/slow/full), preserve image outputs, and handle golden image diffs safely.

# 核心主题

filipstrand filipstrand
[1.9k]
[124]
更新于: 3/10/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
7/11
Quality Score
54
Canonical Locale
en
Detected Body Locale
en

非常适合需要使用pytest和Makefile目标进行高级图像测试和验证的机器学习代理。 Run tests in mflux (fast/slow/full), preserve image outputs, and handle golden image diffs safely.

核心价值

赋予代理快速运行和慢速测试的能力,使用pytest进行图像生成,并使用Makefile目标高效地管理测试工作流,利用MLX原生实现和最先进的生成图像模型。

适用 Agent 类型

非常适合需要使用pytest和Makefile目标进行高级图像测试和验证的机器学习代理。

赋予的主要能力 · mflux-testing

使用`make test-fast`运行不需要图像生成的快速测试
调试失败的测试并分析图像/金标准差异
使用`make test-slow`生成图像进行测试并保留输出以便检查

! 使用限制与门槛

  • 需要pytest进行图像生成测试
  • 需要Makefile目标进行高效测试
  • 保留输出以便检查,但除非明确要求,否则不会更新参考图像

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The page lacks a strong recommendation layer.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

评审后的下一步

先决定动作,再继续看上游仓库材料

Killer-Skills 的主价值不应该停在“帮你打开仓库说明”,而是先帮你判断这项技能是否值得安装、是否应该回到可信集合复核,以及是否已经进入工作流落地阶段。

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

mflux-testing 是什么?

非常适合需要使用pytest和Makefile目标进行高级图像测试和验证的机器学习代理。 Run tests in mflux (fast/slow/full), preserve image outputs, and handle golden image diffs safely.

如何安装 mflux-testing?

运行命令:npx killer-skills add filipstrand/mflux。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

mflux-testing 适用于哪些场景?

典型场景包括:使用`make test-fast`运行不需要图像生成的快速测试、调试失败的测试并分析图像/金标准差异、使用`make test-slow`生成图像进行测试并保留输出以便检查。

mflux-testing 支持哪些 IDE 或 Agent?

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

mflux-testing 有哪些限制?

需要pytest进行图像生成测试;需要Makefile目标进行高效测试;保留输出以便检查,但除非明确要求,否则不会更新参考图像。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add filipstrand/mflux。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    mflux-testing 已启用,可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考,但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论,再决定是否继续查看上游仓库说明。

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

mflux-testing

安装 mflux-testing,这是一款面向AI agent workflows and automation的 AI Agent Skill。查看评审结论、使用场景与安装路径。

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

mflux testing

This repo uses pytest with image-producing tests. Always preserve outputs for inspection and never update reference images unless explicitly asked.

When to Use

  • You need to run tests (fast/slow/full) or debug failing tests.
  • There are image/golden mismatches and you need to report paths/output for review.

Instructions

  • Prefer the Makefile test targets:
    • make test-fast (fast tests, no image generation)
    • make test-slow (slow tests, image generation)
    • make test (full suite)
  • Always keep MFLUX_PRESERVE_TEST_OUTPUT=1 on test runs (already built into the Makefile test targets).
  • If a change affects defaults, config resolution, metadata fields, or CLI behavior, add or update tests that cover the changed behavior directly instead of relying only on manual verification.
  • If tests fail:
    • Summarize the failing test names and the key assertion output.
    • Point to any generated images/artifacts on disk for manual review.
  • Do not regenerate/replace reference (“golden”) images unless the user explicitly requests it.

Manual validation (config resolution + local model paths)

Use when a change touches model config resolution, mflux-save, or the model’s generate CLI, or when a PR fixes local model-path handling for the model under investigation. Refer to the mflux-cli skill to find the correct generate command for the model you are testing.

  • Run a local-path quantize/save:
    • Use the mflux-cli skill to look up the correct command and flags.
    • Verify CLI usage with the command’s --help before running it.
    • Save to a known location (e.g., Desktop) to make follow-up steps explicit.
  • Run generation from the saved model using the correct model-specific generate CLI:
    • Use the mflux-cli skill to find the generate command and required flags.
    • Verify CLI usage with the command’s --help before running it.
  • If the model has multiple size variants, repeat the above for each variant to confirm the correct overrides are applied.
  • Do not commit output artifacts; delete or leave them untracked.

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