suggest_target_table

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

With no annotations provided, the description carries full burden. It discloses it queries live instances, returns a ranked list plus a fallback, and requires user confirmation. Could mention if the call is read-only or has performance implications, but overall sufficient for an interactive suggestion tool.

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 (4 sentences) and well-structured: immediate directive, what it does, return format, and usage instructions. No superfluous information.

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 no output schema, the description adequately explains return format (ranked list + fallback) and how to use the result (present to user, get confirmation). Covers all necessary context for an agent to select and invoke the tool correctly.

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% and each parameter has a clear description. The description adds context ('source platform', 'source object name') and examples but does not significantly augment the schema beyond reinforcing the 'source' aspect. Baseline 3 is appropriate.

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: to query live ServiceNow tables and rank them by similarity to a source object name, intended as a precursor to discover_schema. It distinguishes from siblings like discover_schema and find_table by explicitly using 'BEFORE discover_schema' and 'suggestions'.

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 when-to-use ('when the user has not told you which ServiceNow table to migrate into') and a strong directive to NEVER guess, always call this first. It also instructs to present suggestions and ask for confirmation, covering both usage and alternatives.

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