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NekoTarou

kingbase-mcp-server

by NekoTarou

Preview Table Data

kb_table_data
Read-onlyIdempotent

Preview table data with optional filtering, pagination, and ordering. Supports WHERE conditions, LIMIT/OFFSET, and ORDER BY without writing full SQL.

Instructions

Preview data from a table with optional filtering and pagination.

A convenient shortcut for common SELECT operations without writing full SQL.

Args:

  • table (string): Table name

  • schema (string, optional): Schema name, defaults to DB_SCHEMA env or 'public'

  • limit (number, default 100, max 1000): Number of rows

  • offset (number, default 0): Rows to skip

  • where (string, optional): WHERE condition (without WHERE keyword)

  • order_by (string, optional): ORDER BY clause (without ORDER BY keyword)

Returns: Formatted table of row data with total count.

Examples:

  • table: "users", limit: 10, where: "status = 'active'", order_by: "created_at DESC"

  • table: "orders", limit: 50, offset: 100

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of rows to return (default: 100, max: 1000)
tableYesTable name to preview data from
whereNoOptional WHERE clause (without the WHERE keyword), e.g. "status = 'active'"
offsetNoNumber of rows to skip (default: 0)
schemaNoSchema name (default: from DB_SCHEMA env or 'public')
order_byNoOptional ORDER BY clause (without the ORDER BY keyword), e.g. "created_at DESC"
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already convey read-only, non-destructive, and idempotent behavior. The description adds that it returns a formatted table with total count, enhancing transparency. It does not disclose performance limitations, but given the annotations, the additional context is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured, front-loading the purpose and then detailing parameters and examples. It contains no wasted words, though the examples could be slightly trimmed without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description explains the return format (formatted table with total count). It covers all parameters and examples, fitting well with sibling tools. Minor gaps like performance caveats prevent a perfect score.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage, the baseline is 3. The description adds value through an Args block with defaults and concrete examples (e.g., table: 'users', where: "status = 'active'"), clarifying usage beyond the schema's descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool previews table data with filtering and pagination, using a specific verb and resource. It distinguishes from sibling tools like kb_query, which require full SQL, by positioning itself as a shortcut for common SELECT operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for quick previews without writing SQL, providing clear context. However, it lacks explicit when-not-to-use or direct alternatives like kb_query for complex queries, though sibling context partially compensates.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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