ianva's repos on GitHub
JavaScript · 11 人关注
baya
Baya is a generator that build files and directories. It use a simple config file to build the directory structure you want.
Makefile · 4 人关注
git-rill
创建一个随机命名的 git 分支( heroku-like的命名),不用每次想名字都想的头大了
3 人关注
git-3000
git-3000 是一个git的shell工具合集,拥有要你命3000一样的强大的威力,帮你轻松的完成工作
JavaScript · 1 人关注
impress.js
It's a presentation framework based on the power of CSS3 transforms and transitions in modern browsers and inspired by the idea behind prezi.com.
0 人关注
angular.js
AngularJS - HTML enhanced for web apps!
JavaScript · 0 人关注
antd-dart-scss-theme-plugin
A Webpack plugin for customizing Ant Design with an SCSS theme file and using Ant Design's compiled variables in SCSS files throughout your project.
JavaScript · 0 人关注
ckeditor-dev
The development repository of CKEditor.
0 人关注
codellm-devkit
codellm-devkit provides unified language to get off-the-shelf static analysis for multiple programming languages and support for applying those analyses for code LLM use cases.
VimL · 0 人关注
ctrlp-funky
a ctrlp.vim extension - picks out function defs
0 人关注
Email-Boilerplate
The email boilerplate for sending out nicely formatted messages.
0 人关注
eslint
A fully pluggable tool for identifying and reporting on patterns in JavaScript.
TypeScript · 0 人关注
fetch-md
A CLI tool to fetch web page and convert to markdown
0 人关注
Fiddler
Fiddler for Chrome Extension
Python · 0 人关注
glue
Glue is a simple command line tool to generate CSS sprites
TypeScript · 0 人关注
graphql-seed-faker
🎲 Mock or extend your GraphQL API with faked data. No coding required.
Go · 0 人关注
grimd
:zap: fast dns proxy that can run anywhere, built to black-hole internet advertisements and malware servers
JavaScript · 0 人关注
grunt-jade
Grunt.js plugin to compile jade templates to JavaScript functions (normal or AMD) or plain HTML
JavaScript · 0 人关注
grunt-string-to-js
Grunt task for converting text (HTML/CSS) etc to JavaScript
JavaScript · 0 人关注
holder
Holder renders image placeholders entirely on the client side.
0 人关注
janus-llm
Leveraging LLMs for modernization through intelligent chunking, iterative prompting and reflection, and retrieval augmented generation (RAG).