AskTable Now Supports Claude Code: Let AI Assistants Manage Your Data

What We've Done

AskTable now supports configuration and management through Claude Code.

You can directly chat in Claude Code, letting the AI assistant help you:

• •Upload and manage datasources
• •Optimize metadata to improve query accuracy
• •Configure permission policies
• •Create value indexes and business glossaries

One-sentence understanding: Manage AskTable with natural language, no commands to remember, no web pages to open.

---

What is AskTable Skill

Skill is Claude Code's extension mechanism, giving AI assistants capabilities in specific domains.

AskTable Skill enables Claude Code to:

• •Call all AskTable CLI functions
• •Understand data management best practices
• •Automatically optimize datasource configuration
• •Intelligently suggest indexes and terminology

Think of it as installing a "data management expert" brain into Claude Code.

---

How to Get AskTable Skill

Copy the following instruction and paste it into the Claude Code dialog:

Use npm i -g @datamini/asktable-cli to install the tool, then execute asktable get-skill to get and install the skill

Claude Code will automatically help you complete the installation. According to the Skill installation prompts, enter the relevant API Key to start operating your AskTable.

API Key access: AskTable Console

---

Practical Case: Batch Configure Multiple Datasources, All in One Stop

Let's look at a real enterprise scenario.

Scenario: Integrate All Enterprise Data, Create a Unified Query Entry Point

Your Requirements:

• •1 MySQL database (production order data)
• •1 PostgreSQL database (user behavior data)
• •3 Excel files (sales reports, employee information, product catalog)
• •Need unified query entry point
• •Need to configure permissions: regular employees can only see their own data, management can see all

Traditional Approach:

1. •Open AskTable web pages one by one
2. •Manually create 5 datasources
3. •Configure database connections separately
4. •Upload 3 Excel files
5. •Wait for 5 metadata syncs
6. •Manually optimize each datasource
7. •Create Bot and associate datasources
8. •Configure roles and permission policies
9. •Test if permissions take effect

Estimated Time: 1-2 hours

---

Using Claude Code + AskTable Skill:

You: Help me configure the following datasources and create a unified query Bot:
    1. MySQL database (order data)
       - Host: db.company.com
       - Database: orders
       - User: readonly
    2. PostgreSQL database (user behavior)
       - Host: analytics.company.com
       - Database: user_events
    3. Three Excel files:
       - sales_2024.xlsx (sales reports)
       - employees.xlsx (employee information)
       - products.xlsx (product catalog)

    Permission requirements:
    - Regular employees can only see their own data (filtered by employee_id)
    - Management can see all data

Claude Code:
Okay, I'll batch configure these datasources.

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Step 1: Create Datasources
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[1/5] MySQL Order Data
$ asktable ds create --name "Order Data" --engine mysql \
  --config '{"host":"db.company.com","database":"orders","user":"readonly","password":"***"}'
✓ Datasource created successfully (ID: ds_mysql_001)

[2/5] PostgreSQL User Behavior
$ asktable ds create --name "User Behavior Data" --engine postgres \
  --config '{"host":"analytics.company.com","database":"user_events","user":"readonly","password":"***"}'
✓ Datasource created successfully (ID: ds_pg_001)

[3/5] Excel - Sales Reports
$ asktable ds create --name "Sales Reports" --engine excel
✓ Datasource created successfully (ID: ds_excel_001)
$ asktable ds upload ds_excel_001 sales_2024.xlsx
✓ File uploaded (3.2 MB)

[4/5] Excel - Employee Information
$ asktable ds create --name "Employee Information" --engine excel
✓ Datasource created successfully (ID: ds_excel_002)
$ asktable ds upload ds_excel_002 employees.xlsx
✓ File uploaded (1.1 MB)

[5/5] Excel - Product Catalog
$ asktable ds create --name "Product Catalog" --engine excel
✓ Datasource created successfully (ID: ds_excel_003)
$ asktable ds upload ds_excel_003 products.xlsx
✓ File uploaded (0.8 MB)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Step 2: Sync Metadata
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

$ asktable ds meta sync ds_mysql_001 --wait
✓ MySQL metadata sync completed (15 tables, 127 fields)

$ asktable ds meta sync ds_pg_001 --wait
✓ PostgreSQL metadata sync completed (8 tables, 64 fields)

$ asktable ds meta sync ds_excel_001 --wait
✓ Sales report metadata sync completed (1 table, 12 fields)

$ asktable ds meta sync ds_excel_002 --wait
✓ Employee information metadata sync completed (1 table, 8 fields)

$ asktable ds meta sync ds_excel_003 --wait
✓ Product catalog metadata sync completed (1 table, 10 fields)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Step 3: Intelligent Optimization
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Analyzing key fields, creating value indexes...

$ asktable ds index create ds_mysql_001 --schema orders --table orders --field customer_id
$ asktable ds index create ds_mysql_001 --schema orders --table orders --field product_id
$ asktable ds index create ds_pg_001 --schema public --table events --field user_id
$ asktable ds index create ds_excel_002 --schema public --table employees --field employee_id
$ asktable ds index create ds_excel_003 --schema public --table products --field product_name
✓ Value indexes created for 5 key fields

Adding business terminology...

$ asktable glossary create --term "Active User" --definition "Users who logged in within the last 30 days"
$ asktable glossary create --term "High Value Order" --definition "Orders with amount exceeding 10,000 yuan"
$ asktable glossary create --term "East China" --definition "Includes Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jiangxi, Shandong"
✓ Added 3 business terms

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Step 4: Create Unified Bot
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

$ asktable bot create --name "Enterprise Data Assistant" \
  --datasources ds_mysql_001,ds_pg_001,ds_excel_001,ds_excel_002,ds_excel_003
✓ Bot created successfully (ID: bot_unified_001)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Step 5: Configure Permissions
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

[Create Policy - Employee Self-Check]
$ asktable policy create \
  --name "Employee Self-Check Policy" \
  --permission allow \
  --datasources ds_mysql_001,ds_pg_001,ds_excel_001,ds_excel_002,ds_excel_003 \
  --rows-filter '{"*.*.employee_id": "{{employee_id}}"}'
✓ Policy created successfully (ID: policy_employee)

[Create Policy - Management Overview]
$ asktable policy create \
  --name "Management Overview Policy" \
  --permission allow \
  --datasources ds_mysql_001,ds_pg_001,ds_excel_001,ds_excel_002,ds_excel_003
✓ Policy created successfully (ID: policy_manager)

[Create Roles]
$ asktable role create --name "Regular Employee" --policies policy_employee
✓ Role created successfully (ID: role_employee)

$ asktable role create --name "Management" --policies policy_manager
✓ Role created successfully (ID: role_manager)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Complete! Configuration Summary
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

✓ 5 datasources configured and optimized
  - MySQL: 15 tables, 127 fields
  - PostgreSQL: 8 tables, 64 fields
  - Excel: 3 files, 30 fields

✓ 1 unified query Bot
  - Supports cross-datasource queries
  - Automatically associates related data

✓ 2 roles + 2 permission policies
  - Regular employees: Can only query their own data
  - Management: Can query all data

Now you can use it like this:

[Regular Employee Query]
$ asktable query bot_unified_001 "My sales last month" \
  -r role_employee -V employee_id=E001
→ Only returns data for employee E001

[Management Query]
$ asktable query bot_unified_001 "Last month's total company sales" \
  -r role_manager
→ Returns all data

[Cross-Datasource Query]
$ asktable query bot_unified_001 "Details of top 10 products by sales"
→ Automatically associates order data (MySQL) with product catalog (Excel)

Total time: approximately 3 minutes

Comparison:

• •Traditional approach: 1-2 hours, need to configure one by one
• •Claude Code: 3 minutes, batch completed in one go

---

Core Capabilities

1. Intelligently Optimize Datasources

Claude Code automatically:

• •Identifies key fields (ID, name, amount, date, etc.)
• •Creates value indexes for frequently queried fields
• •Adds business terminology to glossary
• •Optimizes field descriptions and units

Effect: Query accuracy improved by 30%+, response speed improved by 3-5x.

2. Natural Language Management

No commands to remember, just state your needs:

• •"Help me upload this file"
• •"Optimize the employee fields"
• •"Configure permissions, let employees only see their own data"

3. Full Process Automation

From data upload to query optimization, complete in one command:

Help me connect data.xlsx and optimize it

---

Get Started Now

Copy the following instruction and paste it into the Claude Code dialog:

Use npm i -g @datamini/asktable-cli to install the tool, then execute asktable get-skill to get and install the skill

Then say:

Help me upload data.xlsx to AskTable and optimize it

That's it.

---

Why Choose Claude Code + AskTable

Traditional Data Management:

• •Need to learn complex interfaces
• •Manually configure each detail
• •Optimization depends on experience

Claude Code + AskTable:

• •Natural language interaction
• •AI automatically optimizes
• •Best practices built-in

Data management,从此变得简单 (becomes simple from now on).

---

Learn More:

• •AskTable CLI Complete Guide
• •GitHub: AskTable CLI
• •Get API Key