Inspect DDIC Object

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

Beyond the annotations, the description adds meaningful behavioral details: it is read-only, release-independent, accesses DDIC repository tables, and behaves differently by object type. It also discloses error handling, such as empty fields indicating a non-existent or inactive object, which exceeds what annotations alone convey.

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 well-structured with clear headers, concise bullet points, and an immediately useful summary sentence up front. Each section—types, args, returns, examples, error handling—earns its place without redundant filler.

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?

With no output schema, the description compensates by fully specifying the return shape: { objectType, objectName, detail, rawSource? }. It covers all object types, all parameters, examples, and error scenarios. An agent has enough information to select and invoke this tool correctly in the vast majority of cases.

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 schema already covers all parameters at 100%, so the baseline is 3. The description adds value by enumerating what each object type returns, providing concrete examples mapping to values, and clarifying result details. This goes beyond simply restating the schema but does not dramatically deepen parameter understanding.

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 opens with a specific verb and resource: 'Inspect a Data Dictionary object's definition.' It then details distinct behaviors for table, structure, dataelement, domain, and cds, making it unambiguous what this tool does and effectively distinguishing it from sibling tools like sap_get_source or sap_read_table.

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 gives clear context for when to use the tool: any time a DDIC object's definition or metadata is needed. It includes natural-language examples that map user requests to parameters. It does not explicitly state when not to use it or name alternatives, so it falls short of a 5.

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