List Instance Tables

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It does not explicitly state that the operation is read-only, safe, or free of side effects. While the name suggests a listing operation, the description lacks explicit behavioral traits such as idempotency or authorization requirements.

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 concise with no unnecessary words. The first paragraph defines the operation and output, and the second provides differentiation and use cases. Every sentence adds value, making it efficient for an AI agent to parse.

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 7 parameters, 100% schema coverage, and no output schema, the description adequately explains the return values (table name, label, etc.) and contrasts with siblings. However, it could improve by explicitly stating the read-only nature or mentioning pagination (though offset/limit are in schema). Overall, it is largely complete.

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 coverage is 100%, so parameters are fully described in the schema. The description adds minimal extra meaning beyond rephrasing the schema's parameter descriptions. For example, it mentions 'prefix filters, scope filters, and extendable-only mode' but does not provide deeper semantics like formatting or edge cases.

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 lists tables on a ServiceNow instance with optional filtering and specifies the return fields (name, label, parent class, scope, extendable). It distinguishes itself from lookup_table, which searches by name or label keyword, making the purpose unambiguous.

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 contrasts with lookup_table, explaining when to use this tool (browsing with prefix/scope filters, extendable-only mode) and when to use the sibling instead (searching by name or label keyword). This provides clear guidance on tool selection.

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