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run_aggregate_query

Execute grouped aggregate queries (COUNT, SUM, AVG, MIN, MAX) on ServiceNow tables to analyze data by categories like priority or assignment group.

Instructions

Run a grouped aggregate (COUNT, SUM, AVG) query on any table (latest release: /api/now/stats/{table})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesTable to query (e.g., "incident", "task_sla")
group_byYesField to group results by (e.g., "priority", "state", "assignment_group")
aggregateNoAggregate function: COUNT (default), SUM, AVG, MIN, MAX
queryNoOptional encoded query filter
limitNoMax groups (default: 20)
Behavior2/5

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

With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose whether this is a read-only operation, what permissions are required, rate limits, or what happens with invalid parameters. The API endpoint hint is minimal context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core functionality. Every word earns its place with no redundancy or wasted space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a query tool with 5 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain return format, error handling, or typical use cases. The API endpoint hint is insufficient given the complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no additional parameter semantics beyond what's in the schema, but doesn't contradict it. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Run a grouped aggregate (COUNT, SUM, AVG) query on any table' with the specific verb 'run' and resource 'query on any table'. It distinguishes from siblings like 'query_records' or 'trend_query' by specifying aggregate functions, but doesn't explicitly contrast with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 like 'query_records', 'trend_query', or 'get_table_record_count'. It mentions the API endpoint but doesn't explain use cases, prerequisites, or exclusions.

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

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