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Tulip MCP Server

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runTableAggregation

Calculate aggregate statistics like sum, average, or count on table data in Tulip manufacturing platform. Apply filters, sorting, and limits to analyze specific datasets for operational insights.

Instructions

Runs an aggregate function on a table field. Corresponds to GET /tables/{tableId}/runAggregation. Requires tables:read scope. [READ-ONLY]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableIdYesThe ID of the table
functionYesAggregate function name. Valid values: [ "sum", "count", "avg", "min", "max", "mode", "uniqueValues" ]
fieldIdYesThe field to aggregate on.
limitYesThe maximum number of table records to evaluate. Minimum 1, Maximum 100000.
sortOptionsNoSorting allows to define which records are considered if there are more than the specified limit. Sort priority is determined by the order or options. Example: [{"sortBy": "field1", "sortDir": "asc"}]
filtersNoAn optional array of filter expressions to filter the Table records by. Example: [{"field": "field1", "functionType": "equal", "arg": "value1"}]
filterAggregatorNoHow to combine filters, 'all' or 'any'. Default is 'all'.
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds value by specifying the required scope ('tables:read') and marking it as read-only, which clarifies safety and permission needs. However, it lacks details on rate limits, error handling, or what the aggregation output looks like, leaving gaps for a tool with 7 parameters.

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

Conciseness4/5

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

The description is front-loaded with the core purpose and includes essential details like scope and read-only status in a single, efficient sentence. There's no wasted text, though it could be slightly more structured by separating scope from behavioral notes.

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 (7 parameters, no output schema, no annotations), the description is moderately complete. It covers purpose, scope, and safety but lacks output details, error handling, and differentiation from siblings. This is adequate for a read-only operation but leaves the agent guessing about results and alternatives.

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 already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as examples of function usage or filter interactions. This meets the baseline for high schema coverage but doesn't enhance understanding.

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 action ('Runs an aggregate function') and resource ('on a table field'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'getTableAggregation' or 'listTableAggregations', which appear related but have unclear distinctions based on their names alone.

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 by specifying the required scope ('tables:read') and marking it as read-only, which provides some context. However, it doesn't explicitly state when to use this tool versus alternatives like 'getTableAggregation' or 'listTableAggregations', leaving the agent to infer based on naming conventions.

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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