get_table_schema

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

No annotations are present, so the description carries the responsibility of indicating behavior. It communicates that the tool is read-only and returns metadata rather than data, which is the core behavioral trait. However, it does not mention edge-case behavior such as errors when the table or schema does not exist.

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 two short sentences, front-loads what the tool returns, and adds a practical timing guideline with no filler. Every sentence contributes to selecting the tool correctly.

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 simple metadata retrieval tool with two fully documented parameters, the description is largely complete: it names the output fields and gives a usage context. The only minor omission is the absence of a remark about what happens when the schema or table is invalid, but this is not critical for the intended use.

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?

The input schema describes both parameters (table and schema) with examples and 100% coverage. The description adds no parameter-specific meaning beyond what the schema already provides, so the baseline of 3 applies.

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 clearly states a specific verb and resource: it returns the structure (columns, types, length, scale, nullability) of an SAP B1 table. This intrinsically separates it from execute_query and list_tables, though it does not explicitly name a sibling as the differentiator.

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 phrase 'Útil antes de escribir consultas' gives clear context for when to invoke the tool: before forming SQL queries against a table. It does not state exclusions or explicitly discuss alternatives such as list_tables or execute_query.

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