hana_describe_table

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks critical details: it doesn't specify if this is a read-only operation, what permissions are required, what the output format looks like (e.g., column names, types, constraints), or any error conditions (e.g., invalid table names). For a tool with no annotation coverage, this is a significant gap in transparency.

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 ('Describe the structure of a specific table') with zero wasted words. It avoids redundancy and is appropriately sized for a simple tool, making it easy for an agent to parse quickly.

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 for effective tool use. It doesn't explain what 'describe' entails (e.g., returns metadata like columns and data types), potential side effects, or error handling. For a tool with no structured output information, the description should compensate by detailing return values or usage constraints, which it fails to do.

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 description coverage is 100%, with clear documentation for both parameters (schema_name and table_name). The description adds minimal value beyond the schema, as it only implies that table_name is the key input without providing additional context like format examples or relationships between parameters. This meets the baseline for high schema coverage but doesn't enhance 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 clearly states the verb ('describe') and resource ('structure of a specific table'), making the purpose immediately understandable. It distinguishes this from siblings like hana_list_tables (which lists tables) and hana_describe_index (which describes indexes). However, it doesn't explicitly mention the database system (HANA) or differentiate from hana_execute_query, which could also provide structural information through queries.

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 alternatives. It doesn't mention prerequisites (e.g., needing a valid table name), compare it to hana_list_tables for discovery or hana_execute_query for custom queries, or specify use cases like schema exploration or query planning. The agent must infer usage from the tool name and context alone.

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