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dnic-dev

bw-modeling-mcp

by dnic-dev

bw_preview_datasource

Fetch live sample rows from a DataSource and view them as a formatted table with field name headers.

Instructions

Fetch a live data preview / sample rows from a DataSource (RSDS) — reads the first N rows directly from the source system and returns them as a formatted table with field names as column headers. Use this when the user wants to see, sample, preview, or inspect the actual data behind a DataSource (e.g. "show me data from DS_X", "preview 50 rows", "what does DS_X look like"). For data from an aDSO, CompositeProvider, or BEx query, use bw_query_data instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasource_nameYesDataSource name (e.g. "DS_NAME"). Case-insensitive.
source_systemYesLogical source system name (e.g. "LSYS_NAME"). Case-insensitive.
recordsNoNumber of records to fetch (default: 20). SAP returns at most this many rows.
Behavior4/5

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

No annotations provided, so description carries burden. It discloses it reads first N rows, returns formatted table, default 20 records, and SAP caps at that. However, it does not mention permissions or potential performance implications.

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?

Compact and efficient. Front-loads purpose, then usage guidance. Every sentence serves a purpose, no wasted words.

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

Completeness5/5

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

Given no output schema, description mentions return format. Covers purpose, usage, and parameter details adequately for a simple preview tool. No major gaps.

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?

Schema coverage is 100%, baseline 3. Description adds context: case-insensitivity, source system naming, default for records, and SAP behavior. This adds value beyond the schema.

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 it fetches a live data preview from a DataSource, reads first N rows, returns formatted table. It distinguishes itself from bw_query_data for other data types.

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

Usage Guidelines5/5

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

Explicitly tells when to use (user wants to preview data from DataSource) and when not (use bw_query_data for aDSO, CompositeProvider, BEx query), providing an alternative.

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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