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sap_read_table_paginated

Read SAP table data in paginated chunks using offset and limit to handle large result sets without overloading memory.

Instructions

Read table data with pagination support for large result sets. Use offset and limit to page through results. Recommended for tables with 500-5000 rows. For larger tables, consider streaming. Fields in WHERE clause and field_list are validated against table structure. Use sap_get_field_metadata or sap_read_table_structure first to discover correct field names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.1.2

TDQS

A4/5.0
Behavior3/5

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

The description discloses meaningful behavior: pagination via offset and limit, validation of fields against table structure, and row-count recommendations. Since no annotations are provided, the description carries the full burden, but it omits error behavior, response format, and potential rate/auth limitations, so it is only partially transparent.

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 compact, front-loaded with the core purpose, and every sentence adds useful information: pagination mechanics, row-count recommendation, streaming alternative, field validation, and discovery prerequisites. There is no filler or redundancy.

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

Completeness2/5

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

Despite good purpose and usage guidance, the description is not complete enough for reliable invocation: the input schema defines zero parameters while the description references offset, limit, WHERE clause, and field_list, leaving an unresolved contract gap. There is also no output schema or description of the paginated response shape, so the agent cannot fully anticipate the tool's behavior.

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?

The input schema is empty, so the description carries the entire parameter burden and does name the key parameters: offset, limit, WHERE clause, and field_list. It explains their high-level purpose but does not specify types, requiredness, or exact syntax, which prevents a higher score.

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 a specific action ('Read table data with pagination support') and a resource, and it distinguishes this tool from streaming alternatives by recommending it for tables with 500-5000 rows. The large-result-set scope and pagination focus make it easy to tell apart from sibling tools like sap_stream_table_data.

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 gives explicit selection guidance: it is recommended for 500-5000 rows, and larger tables should consider streaming. It also advises using sap_get_field_metadata or sap_read_table_structure first, which is a useful prerequisite. However, it does not explicitly say when to choose this over the other non-streaming table-read siblings.

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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