alibabacloud-data-agent-skill

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29 scripts

Invoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".

4installs
Sourcealiyun/alibabacloud-aiops-skills
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NPX Install

npx skill4agent add aliyun/alibabacloud-aiops-skills alibabacloud-data-agent-skill

Tags

Translated version includes tags in frontmatter
data-analysisalibaba-clouddata-agentcli-tooldatabase-query

SKILL.md Content

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metadata: author: DataAgent Team version: "1.7.2"

Changelog

  • v1.7.2: Use Alibaba Cloud default credential chain instead of explicit AK/SK, add User-Agent header, fix RAM policy wildcard issues
  • v1.7.1: Fix CLI 
    ls
    command API response parsing (support case-insensitive field names), optimize SKILL documentation structure, separate ANALYSIS mode specification document
  • v1.7.0: API_KEY authentication support, native async execution mode, session isolation, enhanced attach mode, optimized log output

Installation

Configure Credentials

This Skill uses Alibaba Cloud default credential chain (recommended) or API_KEY authentication.

Option 1: Default Credential Chain (Recommended)

The Skill uses Alibaba Cloud SDK's default credential chain to automatically obtain credentials, supporting environment variables, configuration files, instance roles, etc.
See Alibaba Cloud Credential Chain Documentation

Option 2: API_KEY Authentication (File Analysis Only)

bash
export DATA_AGENT_API_KEY=your-api-key
export DATA_AGENT_REGION=cn-hangzhou
Get API_KEY: Data Agent Console

Permission Requirements

RAM users need 
AliyunDMSFullAccess
or 
AliyunDMSDataAgentFullAccess
permissions. See RAM-POLICIES.md for detailed permission information.

Debug Mode

bash
DATA_AGENT_DEBUG_API=1 python3 scripts/data_agent_cli.py file example.csv -q "analyze"

💡 Getting Started Tips

  • Use the built-in demo database 
    internal_data_employees
    (DataAgent's built-in test database containing employee, department, and salary data) for first-time experience
  • Or use local file 
    assets/example_game_data.csv
    for file analysis experience

Data Agent CLI — Unified Command-Line Data Analysis Tool

Overview

scripts/data_agent_cli.py
helps users complete the full workflow from discover data → initiate analysis → track progress → get results.

Core Concepts

⚠️ Key Prerequisite: Data Agent can only analyze databases that have been imported into Data Agent Data Center.
  • Data Center: Data Agent's data center, only databases here can be analyzed
  • DMS: Alibaba Cloud Data Management Service, stores metadata of all databases
  • Relationship: Databases registered in DMS ≠ Databases in Data Center
Usage Flow:
  1. First use 
    ls
    to check if the target database exists in Data Center
  2. If not found, use 
    dms
    subcommand to search for database info, then use 
    import
    subcommand to import it
  3. After successful import, you can use 
    db
    subcommand for analysis

Analysis Modes

  • ASK_DATA (default): Synchronous execution, sub-second response, suitable for quick Q&A
  • ANALYSIS: Deep analysis, takes 5-40 minutes, requires spawning a sub-agent for async execution or using --async-run parameter
See ANALYSIS_MODE.md for details

Session Reuse

Use 
db
/
file
to create a session for initial analysis, then use 
attach --session-id <ID>
to reuse the session for follow-up questions.
See COMMANDS.md and WORKFLOWS.md for details

Quick Start

bash
# 1. List available databases
python3 scripts/data_agent_cli.py ls

# 2. Query analysis (synchronous response)
python3 scripts/data_agent_cli.py db \
    --dms-instance-id <ID> --dms-db-id <ID> \
    --instance-name <NAME> --db-name <DB> \
    --tables "employees,departments" -q "Which department has the highest average salary"

# 3. Follow-up question (reuse session)
python3 scripts/data_agent_cli.py attach --session-id <ID> -q "Break down by month"
📖 See WORKFLOWS.md and COMMANDS.md for complete workflows, command reference, and best practices

Project Structure

                          # Skill root directory
├── SKILL.md              # This document
├── scripts/              # Source code
│   ├── data_agent/       # SDK module
│   ├── cli/              # CLI module
│   ├── data_agent_cli.py # CLI entry point
│   └── requirements.txt  # Dependencies
├── sessions/             # Session data
└── references/           # Reference documents