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sonisoft-cnanda

now-sdk-ext-mcp

Grouped Aggregate Query

aggregate_grouped

Compute COUNT, AVG, MIN, MAX, or SUM grouped by a field on a ServiceNow table. Returns per-group statistics for data breakdowns.

Instructions

Run aggregate functions (COUNT, AVG, MIN, MAX, SUM) grouped by a field on any ServiceNow table. Returns per-group statistics — ideal for breakdowns and dashboards.

Examples: count of incidents grouped by priority, average resolution time grouped by category, sum of story points grouped by assignee.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instanceNoThe ServiceNow instance auth alias (e.g., "myinstance", "prod"). If not provided, falls back to the SN_AUTH_ALIAS environment variable.
tableYesThe ServiceNow table name (e.g., "incident", "change_request").
group_byYesThe field name(s) to group by (e.g., ["priority"], ["state", "category"]). Pass a single-element array for simple grouping.
queryNoAn encoded query string to filter records before aggregation.
countNoWhen true, include a COUNT per group.
avg_fieldsNoField names to compute AVG on per group.
min_fieldsNoField names to compute MIN on per group.
max_fieldsNoField names to compute MAX on per group.
sum_fieldsNoField names to compute SUM on per group.
havingNoA HAVING clause to filter groups after aggregation (e.g., "COUNT>10" to only return groups with more than 10 records).
display_valueNoDisplay value handling: "true" returns display values, "false" returns internal values, "all" returns both.
Behavior2/5

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

No annotations are provided, and the description lacks details on performance limits, error conditions, or handling of large datasets. It mentions the instance fallback but not other behavioral traits like rate limits or data volume restrictions.

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 concise (3 sentences plus examples), front-loaded with the key purpose, and every sentence contributes to understanding. No redundant information.

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

Completeness3/5

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

Given the complexity (11 parameters, no output schema), the description does not explain return format, pagination, or error handling. However, the high schema coverage reduces the burden. Adequate but not comprehensive.

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 coverage is 100% with detailed parameter descriptions. The tool description adds value through examples but does not introduce new semantic meaning beyond what the schema provides. Baseline 3 is appropriate.

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

Purpose5/5

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 grouped by a field on ServiceNow tables, listing specific functions (COUNT, AVG, MIN, MAX, SUM) and providing concrete examples. It distinguishes itself from sibling tools like 'aggregate_query' by emphasizing grouping.

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

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for breakdowns and dashboards but does not explicitly specify when to use vs alternatives like aggregate_query. No when-not guidance or mention of prerequisites beyond the schema.

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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