list_hana_schemas

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 discloses the important behavioral scope: it lists only company schemas and excludes system schemas, which is critical for interpreting the result. It does not mention authorization or output format, but for a simple read-only listing tool with zero parameters, these are minor omissions.

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?

Two sentences, no wasted words. The main purpose and exclusion are front-loaded, and the secondary usage hint is placed after the core definition. Every clause earns its place.

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 zero-parameter discovery tool with no output schema, the description is fully complete: it defines the result, the exclusions, and the intended downstream use. An agent has all the information needed to call it correctly and interpret its output.

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?

There are zero parameters, so the baseline is 4 per calibration guidelines. The description adds no parameter-specific detail because none is needed; the behavior itself is fully described.

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 starts with a specific verb 'List' and a clear resource: 'company schemas available on this HANA tenant'. It also adds a precise exclusion ('excludes SAP/HANA system schemas') and distinguishes itself from query tools like query_hana_direct by framing itself as a discovery 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 states a use case: 'Use this to discover valid schema names for query_hana_direct instead of guessing.' This provides clear when-to-use context and names the downstream tool. It does not discuss alternatives or when-not-to-use, but the guidance is strong enough for an agent to know when to invoke it.

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