get_ai_core_topic

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

No annotations are provided, so the description carries the full burden. It states the tool retrieves 'comprehensive documentation,' implying a read-only operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, error handling, or the format/scope of the returned documentation. This leaves significant gaps for a tool with no annotation coverage.

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 a single, efficient sentence that front-loads the core purpose and includes helpful examples. There's no wasted verbiage or redundancy, making it appropriately sized and well-structured for quick understanding.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'comprehensive documentation' entails (e.g., format, depth), how results are structured, or any operational constraints. For a tool with no structured support, this leaves the agent with insufficient context to use it effectively.

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 has 100% description coverage, with the parameter 'topic_name' documented as 'Name of the AI Core topic.' The description adds minimal value by providing examples ('e.g., "Model Training", "Deployment"'), but doesn't elaborate on syntax, allowed values, or constraints beyond what the schema states. This meets the baseline of 3 for high schema coverage.

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 the tool's purpose: 'Get comprehensive documentation for a specific SAP AI Core topic.' It specifies the verb ('Get') and resource ('comprehensive documentation'), and provides examples of topics. However, it doesn't explicitly differentiate from sibling tools like 'get_ai_core_document' or 'search_ai_core_docs', which prevents a score of 5.

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 provides no guidance on when to use this tool versus its siblings. It mentions examples of topics but doesn't specify if this is for general topic overviews versus detailed documentation, or how it differs from 'get_ai_core_document' or 'search_ai_core_docs'. There's no mention of prerequisites, alternatives, or exclusions.

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