Aggregate Query

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is clear. The description adds valuable transparency by stating that it uses the Stats API and returns computed statistics without individual records, which helps the agent anticipate the output. It does not discuss rate limits or authentication, but given annotations cover safety, this is acceptable.

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 two sentences: the first defines the tool's function, the second provides illustrative examples. It is front-loaded, with no redundant phrases or filler content. Every sentence contributes to understanding the tool's purpose and usage.

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 complexity of 9 parameters and no output schema, the description does not explain the exact structure of returned statistics. However, the schema thoroughly documents all inputs, and the description clarifies what the tool returns (computed statistics, not records). The examples provide real-world context. Slight gap in not describing output format, but overall adequate for the tool's complexity.

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%, so each parameter is already well-documented with its own description. The tool description does not add significant parameter-level detail beyond naming the aggregate functions, which maps directly to the array fields (avg_fields, max_fields, etc.). Since the schema carries the semantic load, a baseline score of 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 runs aggregate functions (COUNT, AVG, MIN, MAX, SUM) on ServiceNow tables using the Stats API. It explicitly notes that it returns statistics without individual records, which distinguishes it from query_table and count_records. The inclusion of concrete examples (average resolution time, max priority, etc.) further clarifies the purpose.

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 practical use cases through examples, indicating when the tool is appropriate. However, it does not explicitly mention alternatives or situations where a different sibling tool (e.g., aggregate_grouped or count_records) would be preferred. The phrase 'on any ServiceNow table' implies general applicability, but exclusions are absent.

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