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Agent Skill · 开发

migrate-to-uv(迁移到紫外线)

migrate-to-uv 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

migrate-to-uv 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 18,849。

总安装 312周安装 13GitHub Stars 10下载 104核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:migrate-to-uv(迁移到紫外线)
来源仓库:https://github.com/keboola/ai-kit
仓库路径:skills/migrate-to-uv
安装命令:
npx skills add https://github.com/keboola/ai-kit --skill migrate-to-uv
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/keboola/ai-kit --skill migrate-to-uv

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

migrate-to-uv 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前需确认权限范围和维护状态,注意是否触发联网、命令执行或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/migrate-to-uv

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/keboola/ai-kit --skill migrate-to-uv;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

migrate-to-uv 怎么安装?

在终端执行 npx skills add https://github.com/keboola/ai-kit --skill migrate-to-uv。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

migrate-to-uv 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

migrate-to-uv 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

migrate-to-uv 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

migrate-to-uv 用的人多吗?

公开数据是累计安装 312 次,近一周安装 13 次,下载 104 次,GitHub 10 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

migrate-to-uv 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
migrate-to-uv

迁移到紫外线 · 本页

31210需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Migrate to uv Build System

Migrate a Keboola component (Docker-based, ECR-deployed) from requirements.txt + pip to pyproject.toml + uv with ruff linting.

Execute all steps yourself using the tools available to you. Do NOT delegate to or invoke any other agent (component-builder, develop-component, or similar) — except component-developer:component-defaults in Phase 6.

You MUST complete every step below. Do not skip any step — if a file doesn't exist, move on silently.


Step 0: Read the current state

cat requirements.txt
grep "FROM python:" Dockerfile
cat .github/workflows/push.yml

Commit 1: migrate to pyproject.toml 📦

Create pyproject.toml

Create a minimal pyproject.toml with metadata and ruff config but no dependencies yet — you'll populate those with uv add next:

  • Always use requires-python = "~=3.13.0" and target-version = "py313"
  • Leave dependencies = [] empty for now

Then populate dependencies from requirements.txt using uv:

# Add all main deps at once
uv add -r requirements.txt

# Move test-only deps to the dev group (common ones: pytest, mock, freezegun, responses)
# For each test dep found in requirements.txt:
uv remove <test-dep>
uv add --group dev <test-dep>

uv add auto-converts pinned versions to >= ranges and updates uv.lock in place — no manual conversion needed.

Delete files

rm -f requirements.txt
rm -f .flake8 flake8.cfg
rm -f scripts/build_n_run.ps1 scripts/run.bat scripts/run_kbc_tests.ps1
rm -f scripts/update_dev_portal_properties.sh
rm -rf docs/imgs/
rm -f component_config/configuration_description.md component_config/stack_parameters.json

(rm -f silently does nothing if a file doesn't exist — no errors, no stopping.)

Populate component_config/ URLs (if the files are currently empty)

component_config/documentationUrl.md  → https://github.com/keboola/REPO/blob/master/README.md
component_config/licenseUrl.md        → https://github.com/keboola/REPO/blob/master/LICENSE.md
component_config/sourceCodeUrl.md     → https://github.com/keboola/REPO

Update .gitignore

Add these lines if not present:

*.egg-info/
.venv/
.DS_Store
/data

Replace bare data/ with /data. Remove duplicate .vscode/ entries.

Commit

git add -u                                          # stages all deletions
git add pyproject.toml uv.lock .gitignore component_config/
git commit -m "migrate to pyproject.toml 📦"

Commit 2: uv 💜

Update Dockerfile

Use the multi-stage build pattern. The base stage is shared by both test and production — keeping the production image lean (no dev deps, no test files).

FROM python:3.13-slim AS base
COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/

# apt-get installs MUST come before uv sync
# RUN apt-get update && apt-get install -y <packages>  ← keep if already present

WORKDIR /code/
COPY pyproject.toml uv.lock ./
ENV UV_PROJECT_ENVIRONMENT="/usr/local/"
RUN uv sync --no-dev --frozen

COPY src/ src/
COPY scripts/ scripts/
COPY deploy.sh .

FROM base AS test
RUN uv sync --all-groups --frozen
COPY tests/ tests/
RUN uv run ruff check src/ tests/
CMD ["uv", "run", "pytest", "tests/", "-v"]

FROM base AS production
CMD ["python", "-u", "/code/src/component.py"]

Notes:

  • base installs only production deps (--no-dev); test adds dev deps on top
  • Ruff check runs at image build time in the test stage — failing fast
  • ENV KEY="value" syntax (not old ENV KEY value)
  • No pip install anywhere
  • Any apt-get blocks must stay before RUN uv sync

Update scripts/build_n_test.sh

#!/bin/sh
set -e

ruff check
python -m pytest tests/ --tb=short -q

Update tests/__init__.py

Replace old os.path pattern:

import sys
from pathlib import Path
sys.path.append(str(Path(__file__).resolve().parent.parent / "src"))

Update .github/workflows/push.yml

The canonical push.yml uses a multi-job pipeline that matches the multi-stage Dockerfile. Rather than patching individual steps, replace the file entirely with the canonical template (from Phase 6 / component-defaults) and update only the env: block for this component:

env:
  KBC_DEVELOPERPORTAL_APP: "vendor.component-id"   # full component ID from Developer Portal
  KBC_DEVELOPERPORTAL_VENDOR: "vendor"              # your vendor name
  DOCKERHUB_USER: ${{ secrets.DOCKERHUB_USER }}
  KBC_DEVELOPERPORTAL_USERNAME: ${{ vars.KBC_DEVELOPERPORTAL_USERNAME }}
  DOCKERHUB_TOKEN: ${{ secrets.DOCKERHUB_TOKEN }}
  KBC_DEVELOPERPORTAL_PASSWORD: ${{ secrets.KBC_DEVELOPERPORTAL_PASSWORD }}
  KBC_TEST_PROJECT_CONFIGS: ""
  KBC_STORAGE_TOKEN: ${{ secrets.KBC_STORAGE_TOKEN }}

The new pipeline structure (keep as-is from the canonical template):

  • push_event_info — branch/tag detection, is_deploy_ready output (requires default branch + semantic tag)
  • build-test — builds --target test stage, uploads as *-test.tar artifact
  • tests — downloads test artifact, runs container (default CMD = pytest; ruff already ran at build time)
  • tests-kbc — runs KBC integration tests if KBC_TEST_PROJECT_CONFIGS and token are set
  • build-production — builds --target production stage after all tests pass, uploads as *.tar artifact
  • push — loads production artifact, pushes to ECR
  • deploy — sets tag in Developer Portal, only if is_deploy_ready == true
  • update_developer_portal_properties — runs scripts/developer_portal/update_properties.sh

Generate / verify lock file

uv add already updated uv.lock during Commit 1. Run this to ensure it's fully consistent:

uv sync --all-groups

Commit

git add Dockerfile scripts/ tests/ .github/workflows/
git commit -m "uv 💜"

Commit 3: ruff linting baseline 🎨

ruff format .
ruff check --fix .

Commit if any files changed:

git add src/ tests/
git commit -m "ruff linting baseline 🎨"

Phase 6: Cookiecutter Alignment Check

Use the Task tool to load the canonical template files:

  • subagent_type: component-developer:component-defaults
  • prompt: "Return the canonical Keboola component template files."

Then compare each of the following against the returned canonical versions:

Component fileCanonical
Dockerfilefrom component-defaults
.github/workflows/push.ymlfrom component-defaults
scripts/build_n_test.shfrom component-defaults
docker-compose.ymlfrom component-defaults
.pre-commit-config.yamlfrom component-defaults

Fix structural differences. Keep component-specific additions (custom apt packages, SSL certs, etc.). Create missing files from the canonical version (.pre-commit-config.yaml is often absent in old components).

git add Dockerfile scripts/ .github/workflows/ docker-compose.yml .pre-commit-config.yaml
git commit -m "align with cookiecutter template 🍪"

Verify

# Build and run tests (ruff runs at build time inside the test stage)
docker build --target test -t test-component .
docker run test-component

# Optionally verify the production image builds cleanly
docker build --target production -t prod-component .

Common Patterns

Dependency conversion:

requirements.txt          pyproject.toml
keboola.component==1.4.4  "keboola-component>=1.4.4"
mock                      "mock>=5.2.0"  (in dev group)

Ruff config (always use "UP" for pyupgrade):

[tool.ruff]
line-length = 120
target-version = "py313"

[tool.ruff.lint]
extend-select = ["I", "UP"]

平台分布

Codex

34.08%
按下载量换算35

Claude

30.94%
按下载量换算32

Cursor

20.92%
按下载量换算22

Gemini CLI

9.01%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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