sap_count_rows

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

With no annotations provided, the description carries the full behavioral burden. It discloses that the count is estimated, that the tool returns a recommendation, and that it is intended as a pre-fetch check. It could add caveats about estimation accuracy, but the core behavioral traits are clear.

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

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

The description is three short sentences with no filler. Purpose, usage context, output, and priority guidance are all front-loaded, and every sentence earns its place.

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

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

For a zero-parameter preflight tool, the description covers what it does, when to use it, what it returns, and concrete table examples. The only notable gap is that it never clarifies how the target table is identified given the empty input schema, but the rest is self-contained.

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

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

There are zero parameters, so the baseline of 4 applies. The description adds meaning by explaining what the tool does with the underlying table, even though the input schema has no formal parameters to document.

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

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

The description uses a specific verb and resource: 'Estimate row count for a table' before fetching data. It clearly distinguishes this from data-retrieval siblings by emphasizing it returns a count and a recommendation rather than table contents.

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

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

The description explicitly says to use this before querying large tables like BKPF, EKKO, and VBAK without date filters, and to check for oversized result sets. It does not explicitly name sibling tools to use instead, but the recommendation values (direct_read, use_pagination, use_streaming) imply the follow-up decision.

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