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advai-cli-unified-terminal-ai
Unified CLI for local skills, external CLIs, and terminal AI chat with multi-platform skill sync support.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Unified CLI for local skills, external CLIs, and terminal AI chat with multi-platform skill sync support.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
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| name | advai-cli-unified-terminal-ai |
| description | Unified CLI for local skills, external CLIs, and terminal AI chat with multi-platform skill sync support. |
| triggers | ["install or manage AI coding agent skills","sync skills to Cursor, Claude Code, or other platforms","start a terminal AI chat session","manage external CLIs through advai","create a local knowledge base","configure advai-cli with OpenAI-compatible API","list available skills and platforms","update or uninstall advai skills"] |
Skill by ara.so — Devtools Skills collection.
advai-cli is a unified command-line interface that consolidates local skill management, external CLI workflows, and terminal-native AI chat through a single advai entrypoint. It provides a Python-first core with npm and Homebrew distribution options, supporting 51+ built-in platform adapters including Cursor, Claude Code, Codex, TRAE, Cline, Continue, and more.
pip install advai-cli
npm install -g advai-cli
The npm package creates a private Python virtual environment and installs the PyPI package during postinstall.
brew tap Advai-X/tap
brew install advai-cli
advai --help
advai info
~/.advai/skills# Required for AI features
export ADVAI_API_KEY="your_api_key"
# Optional configuration
export ADVAI_BASE_URL="https://api.openai.com/v1"
export ADVAI_MODEL="gpt-4o-mini"
export ADVAI_AGENT="default"
export ADVAI_SYSTEM_PROMPT="You are a helpful coding assistant."
export ADVAI_TIMEOUT="120"
# Fallback to standard OpenAI naming
export OPENAI_API_KEY="your_api_key"
export OPENAI_BASE_URL="https://api.openai.com/v1"
export OPENAI_MODEL="gpt-4o-mini"
Local state and skills are stored in ~/.advai/:
~/.advai/
├── skills/ # Installed skill definitions
├── cli/ # External CLI metadata
├── kb/ # Knowledge bases
└── config.json # User configuration
advai skill list
# Install all skills from a repo
advai skill install https://github.com/your-org/skill-repo
# Install a specific skill
advai skill install https://github.com/your-org/skill-repo --skill demo-skill
# Install and sync to a platform immediately
advai skill install https://github.com/your-org/skill-repo --skill demo-skill --platform cursor
advai skill info demo-skill
# Update a specific skill
advai skill update demo-skill
# Update all installed skills
advai skill update
advai skill uninstall demo-skill
advai skill platform list
Displays 51+ built-in platforms including:
# Sync to Cursor
advai skill sync demo-skill --platform cursor
# Sync to multiple platforms
advai skill sync demo-skill --platform trae --platform claude_code
# Sync with project-specific directory (e.g., for omp_agent)
advai skill sync demo-skill --platform omp_agent --project-dir /path/to/repo
advai skill unsync demo-skill --platform cursor
advai skill platform add custom_agent --name "Custom Agent" --path ~/.custom-agent/skills
# Override default platform directory
advai skill platform override cursor --path ~/.cursor/skills
# Clear override and return to default
advai skill platform clear-override cursor
Requires opencli binary for full functionality.
advai cli list
advai cli info gh
advai cli install https://github.com/cli/cli
advai cli install https://github.com/cli/cli --cli gh
advai cli update gh --yes
advai cli uninstall gh --yes
advai cli gh repo list
advai cli docker ps
# Start with default configuration
advai tui
# Specify model
advai tui --model gpt-4o-mini
# Use custom base URL
advai tui --base-url https://api.openai.com/v1
# Set system prompt
advai tui --system-prompt "You are a concise terminal coding assistant."
# Configure timeout
advai tui --timeout 180
# Use specific agent
advai tui --agent default
/help # Show available commands
/clear # Clear conversation history
/agent # Open interactive agent picker
/agent default # Switch to specific agent
/model # Open interactive model picker
/model gpt-4o-mini # Switch to specific model
/system You are a helpful assistant. # Update system prompt
/save ./chat.md # Export conversation transcript
/exit # Exit TUI
# The TUI is CLI-only, but the underlying client can be used programmatically
from advai_cli.client import AdvaiClient
client = AdvaiClient(
api_key="your_api_key",
base_url="https://api.openai.com/v1",
model="gpt-4o-mini",
timeout=120
)
response = client.chat_completion(
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Explain Python decorators"}
]
)
print(response["choices"][0]["message"]["content"])
advai kb create project-docs
advai kb doc add project-docs ./README.md
advai kb doc add project-docs ./docs/api.md
advai kb search project-docs "authentication flow"
# Refresh all documents from their original paths
advai kb sync project-docs
#!/usr/bin/env python3
"""
Setup script to install and configure advai-cli skills
"""
import subprocess
import os
def setup_advai():
# Install advai-cli
subprocess.run(["pip", "install", "advai-cli"], check=True)
# Configure API key
api_key = os.getenv("OPENAI_API_KEY")
if not api_key:
raise ValueError("OPENAI_API_KEY environment variable required")
# Install project-specific skills
skills_repo = "https://github.com/your-org/team-skills"
subprocess.run([
"advai", "skill", "install", skills_repo,
"--skill", "python-best-practices"
], check=True)
# Sync to active platforms
platforms = ["cursor", "claude_code", "continue"]
for platform in platforms:
subprocess.run([
"advai", "skill", "sync", "python-best-practices",
"--platform", platform
], check=True)
print("✓ advai-cli configured with team skills")
if __name__ == "__main__":
setup_advai()
# Install multiple skills and sync to Cursor
for skill_url in \
"https://github.com/team/skill-python" \
"https://github.com/team/skill-typescript" \
"https://github.com/team/skill-testing"
do
advai skill install "$skill_url" --platform cursor
done
# Update all skills at once
advai skill update
# List what's installed
advai skill list
#!/usr/bin/env python3
"""
Deploy skills across multiple agent platforms
"""
import subprocess
import sys
SKILL_NAME = "team-coding-standards"
PLATFORMS = [
"cursor",
"claude_code",
"codex",
"trae",
"cline",
"continue"
]
def deploy_skill(skill_name: str, platforms: list[str]):
"""Deploy a skill to multiple platforms"""
for platform in platforms:
try:
result = subprocess.run(
["advai", "skill", "sync", skill_name, "--platform", platform],
check=True,
capture_output=True,
text=True
)
print(f"✓ Synced {skill_name} to {platform}")
except subprocess.CalledProcessError as e:
print(f"✗ Failed to sync to {platform}: {e.stderr}", file=sys.stderr)
if __name__ == "__main__":
deploy_skill(SKILL_NAME, PLATFORMS)
your-skill-repo/
├── skills/
│ ├── python-patterns/
│ │ └── SKILL.md
│ ├── api-design/
│ │ └── SKILL.md
│ └── testing-practices/
│ └── SKILL.md
└── README.md
Install from this structure:
# Install all skills
advai skill install https://github.com/your-org/your-skill-repo
# Install one specific skill
advai skill install https://github.com/your-org/your-skill-repo --skill python-patterns
# Show runtime, version, and install method
advai info
Output includes:
# Shows recommended update command for your install method
advai update
# Check API key is set
echo $ADVAI_API_KEY
# Test API connection
export ADVAI_API_KEY="your_key"
advai tui --model gpt-4o-mini
# Verify platform is recognized
advai skill platform list | grep cursor
# Check platform path
advai skill platform override cursor --path ~/.cursor/skills
# List installed skills
advai skill list
# Try manual sync with verbose output
advai skill sync my-skill --platform cursor
# Ensure Node.js 14+ and Python 3.8+ are installed
node --version
python3 --version
# Reinstall with clean cache
npm uninstall -g advai-cli
npm cache clean --force
npm install -g advai-cli
# Ensure repo has skills/ directory at root
# Check if you need to specify --skill flag
advai skill install https://github.com/org/repo --skill specific-skill
# Verify GitHub URL is accessible
curl -I https://github.com/org/repo
# Check if platform directory exists
ls -la ~/.cursor/skills/
# Create directory if needed
mkdir -p ~/.cursor/skills/
# Override platform path if non-standard
advai skill platform override cursor --path /custom/path/skills
# Verify KB exists
ls -la ~/.advai/kb/
# Resync documents from source
advai kb sync project-docs
# Check document paths are still valid
advai kb doc add project-docs ./path/to/file.md
ADVAI_API_KEY or OPENAI_API_KEYadvai skill update to get latest skill definitionsadvai skill platform add for internal or proprietary agents--project-dir flag for project-scoped agents like omp_agent/save command to keep transcript recordsadvai kb sync after updating source documents# .github/workflows/deploy-skills.yml
name: Deploy Skills
on:
push:
branches: [main]
paths:
- 'skills/**'
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install advai-cli
run: pip install advai-cli
- name: Deploy skills
env:
ADVAI_API_KEY: ${{ secrets.ADVAI_API_KEY }}
run: |
advai skill install . --skill team-standards
advai skill list
#!/bin/bash
# .git/hooks/pre-commit
# Ensure skills are synced before committing
advai skill update
advai skill sync team-standards --platform cursor
echo "✓ Skills synced"
FROM python:3.11-slim
RUN pip install advai-cli
ENV ADVAI_API_KEY=""
ENV ADVAI_MODEL="gpt-4o-mini"
# Install team skills at build time
RUN advai skill install https://github.com/team/skills --skill coding-standards
CMD ["advai", "tui"]