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aficiomaquinas

mcp-baserow-schema

list_rows

Retrieve rows from a Baserow table with pagination, full-text search, and sorting. Returns human-readable field names for easy integration.

Instructions

List rows from a table with pagination, search, and sorting. Returns field values using human-readable field names by default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (1-indexed). Default: 1.
sizeNoNumber of rows per page. Default: 100.
searchNoSearch query to filter rows. Uses full-text search.
order_byNoComma-separated field names to sort by. Prefix with - for descending. Example: "Name,-Created On".
table_idYesThe table ID to list rows from.
Behavior3/5

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

With no annotations, the description carries the burden of disclosing behavior. It adds the useful trait that field values are returned using human-readable names by default. However, it does not explicitly state that the operation is read-only or describe pagination limits/response structure, which are relevant behavioral details.

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

Conciseness5/5

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

The description is a single, front-loaded sentence that conveys the core action and key features with no redundant phrases. It is highly concise and well-structured.

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

Completeness3/5

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

Without an output schema, the description should explain return values. It mentions human-readable field names but does not describe the overall response structure (e.g., whether pagination metadata is included). The absence of annotations also leaves safety/read-only expectations implicit, so the description is only partially complete.

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

Parameters3/5

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

The input schema covers all 5 parameters with descriptions, so the baseline is 3. The description mentions pagination, search, and sorting, which map to parameters, but adds no additional semantic detail beyond what the schema already provides.

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 operation (list rows from a table) and specific capabilities (pagination, search, sorting). This distinguishes it from sibling tools like list_tables and list_fields, which deal with different resources.

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 provides clear context for when to use this tool: when needing to read rows with optional filtering/sorting. However, it does not explicitly mention alternatives or when not to use it, leaving room for ambiguity relative to other row operations like create_row or update_row.

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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