query_sml_view

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

With no annotations supplied, the description carries the transparency burden. It discloses the HTTP method ('Simple OData GET'), service context, and provides concrete filter/status syntax examples. It could also mention pagination or server limits, but the schema already notes that omitting top returns all records; overall, enough behavioral context is provided for a read-only query tool.

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 the length is justified by the extensive catalog of valid view names and filter examples, which directly supports correct invocation. It is well-structured with clear section headers and front-loads the core purpose in the first sentence, keeping the important guidance easy to scan.

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?

Given the tool's complexity and absence of an output schema, the description is substantially complete: it covers available views, common fields, date-filter patterns, and status values. It lacks explicit guidance on when NOT to use it versus closely related query tools, but the provided context is sufficient for most analytics and reporting scenarios.

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. The description adds meaningful value by enumerating valid view names, common fields per view type, and OData date-filter and status-filter patterns. This goes beyond the schema's plain parameter descriptions and helps construct correct 'filter' and 'viewName' values.

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 identifies the specific verb ('Query'), the resource ('SAP B1 Standard HANA Model view via sml.svc'), and the intended domain ('all analytics, reporting, and document queries'). It differentiates from raw query siblings by emphasizing the SML service and 'no namespace needed', though it does not explicitly name an alternative tool.

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 'Use this for all analytics, reporting, and document queries', giving a clear primary context. It does not provide explicit exclusions or name sibling alternatives like query_hana_direct or query_sql_direct, but the domain framing and view list guide appropriate usage.

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