sap_multi_table_query

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

With no annotations provided, the description carries the full burden, and it delivers: it discloses the requires_confirmation flow for >1000 rows, the timeout risk of querying full master tables without depends_on, and that fields are validated against table structure. It even warns against a common failure mode (KNA1 returning 100K+ customers) and prescribes the behavior of asking the user before showing large results.

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 long but densely packed and clearly marked (SUPPORTS AGGREGATION, IMPORTANT, CRITICAL, NOTE, Example), front-loading the purpose before operational warnings. Nearly every section earns its place given the tool's complexity, though the aggregation intro slightly duplicates what the schema already documents.

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 highly complex tool with nested query_plan objects and no output schema, the description thoroughly covers query planning pitfalls, confirmation behavior, and field discovery. The main gap is that it never describes the successful response format (structure of merged results), and it doesn't differentiate itself from the similarly named sap_smart_table_query sibling — though the coverage of operational essentials is strong enough that agents can call it correctly.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds strategic meaning beyond the schema's parameter docs: it explains why depends_on/filter_field exist (avoiding timeouts) with a concrete KNA1 example, clarifies when confirmed should be set (only after user consent), and shows the sort_by+sort_order+limit pattern for recency queries. This elevates it to 4, though individual parameter details still live mostly in the schema.

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 states a specific verb-resource pair ('Execute a multi-table query with proper joins and optional aggregation') and a crisp scope criterion ('data from 2+ tables that must be merged'). It explicitly differentiates from the key sibling tool: 'Use this instead of multiple sap_read_table_data calls when you need joined data!'

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?

Provides explicit when-to-use guidance ('Use this when you need data from 2+ tables that must be merged'), names the alternative (sap_read_table_data), and gives conditional routing rules: use aggregation for 'top N' queries, use depends_on/filter_field for master data lookups, and use sort_by+sort_order+limit instead of confirmed=true for 'last N' requests. No ambiguity about when this tool applies.

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