BytesAgain is a curated directory of 60,000+ AI agent skills from ClawHub, GitHub, LobeHub, and Dify. Search skills by keyword in 7 languages, browse by role (developer, creator, trader, marketer) or by use case.

How do I find AI skills on BytesAgain?

Use the search bar on BytesAgain.com to search by keyword in 7 languages. You can also browse by role (developer, creator, trader, marketer) or by use case. Each skill shows install instructions for Claude, Cursor, OpenClaw, Continue, and more.

Yes, BytesAgain is completely free. No registration required for searching skills. The MCP API is also free with rate limits.

Does BytesAgain have an API for AI agents?

Yes! BytesAgain provides a free MCP SSE endpoint at /api/mcp/sse for AI agents, plus a REST API at /api/mcp?action=search&q= . No authentication needed.

Can I request a new AI skill on BytesAgain?

Yes! Visit the Requests page on BytesAgain.com to submit a skill request. Your request will be visible to the community and notified to the site admin.

🦀 ClawHub

Alibabacloud Data Agent Skill

by @sdk-team

Invoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analyti...

Versionv1.8.5

Downloads657

#crypto-defi #devops #data #translation #legal

View on ClawHub →

TERMINAL

clawhub install alibabacloud-data-agent-skill

📖 About This Skill

name: alibabacloud-data-agent-skill description: | 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". compatibility: | Requires valid Alibaba Cloud credentials (default credential chain or API_KEY); Requires dependencies in requirements.txt to be installed; Data sources must be managed in Alibaba Cloud Apsara Database or DMS. domain: AIOps

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)

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

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 to reuse the session for follow-up questions.

> See COMMANDS.md and WORKFLOWS.md for details

Quick Start

# 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  --dms-db-id  \
    --instance-name  --db-name  \
    --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  -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

💡 Examples

# 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  --dms-db-id  \
    --instance-name  --db-name  \
    --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  -q "Break down by month"

> 📖 See WORKFLOWS.md and COMMANDS.md for complete workflows, command reference, and best practices