Discover Table Schema

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

With annotations declaring readOnlyHint=true and openWorldHint=true, the description adds value by detailing what will be returned (table name, label, parent class, per-field attributes) and explaining that optional flags query additional data sources like sys_choice. It does not contradict the annotations and provides useful context about the read-only, exploratory nature of the operation.

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 and concise. It opens with a clear summary sentence, follows with a compact return-value list, and then uses bullet points for key use cases. Every sentence provides useful information without redundancy or fluff.

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?

The tool has six parameters and no output schema, but the description compensates by explaining the return structure and the effects of optional flags. It covers the main use cases and clearly indicates the optional data that can be included. However, it does not exhaustively describe all edge cases or behavior for invalid tables, which keeps it slightly below a perfect score.

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 already provides comprehensive descriptions for all six parameters, including examples and defaults (e.g., 'include_choices: Include choice values for fields that have them'). The tool description restates some of this information (e.g., 'optionally choice values') but does not add significant new semantics beyond the schema.

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: 'Discover the full schema of a ServiceNow table including all fields, types, references, and optionally choice values, relationships, UI policies, and business rules.' This is a specific verb-resource combination that distinguishes it from sibling tools like lookup_table or explain_field by focusing on comprehensive schema discovery.

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 explicit use cases: 'Understand the structure of a table before querying or scripting against it', 'Discover reference fields', 'Find choice values', and 'Review UI policies and business rules'. This gives clear context for when to use the tool, though it does not explicitly mention alternatives or when not to use it.

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