Converts Figma frames into front-end code for various mobile frameworks.

aica
aica(AI Code Analyzer) reviews your code using AI. Supports CLI and GitHub Actions.
3 years
Works with Finder
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aica - AI Code Analyzer
Motivation
There are already excellent code review tools such as pr-agent and cursor. However, pr-agent relies on code hosting services like GitHub, which limits its usability, and cursor is not open source, meaning it cannot be fully customized or integrated with other tools.
So, I decided to create a new tool with the following characteristics:
- Customizable
- Open Source
- Platform Independent
Features
- AI Coding Agent
- AI Code Review
- MCP(Model Context Protocol) supported. stdio and SSE transports are supported.
- Automatic knowledge retrieving for code review
- Symbol based code search for retrieving knowledge
- Vector based document search for retrieving knowledge
- Generate summary of changes
- Generate commit message
- Create pull request with AI-generated title and body
- Prompt customization
- Slack notification
- Single binary executable by
bun build --compile
- GitHub Actions integration. (See wiki page to setup actions.)
Install
Build and install a binary:
# Install bun before build aica.
#
# Official Install Document:
# https://bun.sh/docs/installation#installing
git clone https://github.com/dotneet/aica.git
cd aica
bun install
bun run build
cp ./dist/aica path-to-your-bin-directory
Setup GitHub Token:
# if GITHUB_TOKEN is not set, aica try to get token from `gh auth token`.
export GITHUB_TOKEN=your_github_token
Setup LLM:
# You can set the following items in your environment variables or aica.toml file.
# Configure at least one of the following providers:
# Anthropic (If you use agent, strongly recommend to use claude sonnet model)
export AICA_LLM_PROVIDER=anthropic
export ANTHROPIC_API_KEY=your_api_key
export ANTHROPIC_MODEL=claude-3-5-sonnet-20241022
# OpenAI
export AICA_LLM_PROVIDER=openai
export OPENAI_API_KEY=your_api_key
export OPENAI_MODEL=o3-mini
# Gemini
export AICA_LLM_PROVIDER=google
export GOOGLE_API_KEY=your_api_key
export GOOGLE_MODEL=gemini-2.0-flash
Configuration
You can customize the configuration by creating a aica.toml
file.
See aica.example.toml.
aica.toml must be placed in one of the following directories.
- root directory of the repository
- ${HOME}/.config/aica/aica.toml
- ${GITHUB_WORKSPACE}/aica.toml
Language
You can specify the language for AI output. The language can be specified either through AICA_LANGUAGE or in the language section of aica.toml. By default, the language is automatically detected from the LANG environment variable.
export AICA_LANGUAGE=Japanese
Priority:
-
AICA_LANGUAGE
-
language.language
in aica.toml - Automatic detection from
LANG
Usage
Review
# review the diff from HEAD
aica review [options] [pattern]
# review specific files
aica review src/main.ts
# review the files matching the specific glob pattern
aica review "src/**/*.ts"
Options:
-
--dir
: Target directory path -
--slack
: Send notification to Slack
Agent
# execute AI agent with a prompt
aica agent "your prompt here"
# execute AI agent with a instruction file
aica agent -f instruction.txt
# conversation mode. You can interact with AI agent by typing your prompt.
aica agent
This command executes a task using an AI agent. The agent automatically determines and executes the necessary actions based on the given prompt.
Recommend to use anthropic claude 3.5 sonnet for agent.
NOTE: This command has potential to break your file system. Please be careful.
Aica Agent as an MCP Server
# start a MCP server
aica mcp server
# start a MCP server with a config file
aica mcp server --config aica.toml
Reindex
# reindex the code and document databases
aica reindex
Summary
# generate a summary of the diff from HEAD
aica summary [options]
Options:
-
--dir
: Target directory path
Commit Changes
This command commits changes with an AI-generated commit message.
# commit all changes(including untracked and unstaged changes) with an AI-generated commit message
aica commit [options] # commits all changes (including untracked and unstaged changes) with an AI-generated commit message
aica commit --staged # commits only staged changes with an AI-generated commit message
aica commit --push # commits all changes and pushes to remote repository
Options:
-
--staged
: commit only staged changes. -
--dryRun
: Show result without execution -
--push
: Push to remote repository after committing
Create Pull Request
This command creates a pull request on GitHub.
# Creates a pull request. If there are changes, they will be committed automatically.
aica create-pr [options]
# Creates a pull request with only staged changes
aica create-pr --staged
Options:
-
--withSummary
: Generate summary of diff from HEAD (default: true) -
--body
: Pull request body -
--dryRun
: Show result without execution -
--staged
: Only include staged changes
Generate Commit Message
# generate a one-line commit message based on the diff from HEAD
aica commit-message [options]
Options:
-
--dir
: Target directory path
Show Configuration
# show current configuration
aica show-config [options]
Options:
-
--default
: Show default configuration
Other Commands
-
aica --version
: Show version information -
aica --help [command]
: Show help information for a specific command or general help
Add Context
.cursorrules and .clinerules are automatically added to the context. To customize the context, configure the [rules] section in aica.toml.
Additionally, .cursor/rules/*.mdc files are supported by default. This function can be disabled through the settings.
MCP(Model Context Protocol)
create a mcp.json file to define the MCP server.
example:
[
{
"name": "example-server",
"type": "stdio",
"command": "node",
"args": ["./server.js"]
},
{
"name": "example-server",
"type": "sse",
"url": "http://localhost:3001/sse"
}
]
set setupFile
in aica.toml like below.
[mcp]
setupFile = "mcp.json"
GitHub Actions
Setup
See wiki page for details.
Commands
You can interact with AI features by leaving comments with the following commands.
# edit the code with AI
/aica edit "your prompt here"
# update summary in the pull request body
/aica summary
# review the latest diff
/aica review
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Reviews

user_k2MZtJB5
I recently started using aica by dotneet, and I'm thoroughly impressed. The application is robust and user-friendly, making my tasks much more manageable. The documentation on the GitHub page is comprehensive and easy to follow. As a dedicated MCP application fan, I highly recommend aica for anyone looking for a reliable and efficient tool. Check it out at https://github.com/dotneet/aica!