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tulip

Tulip MCP Server

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by tulip

countTableRecords

Count records in a Tulip Table to monitor data volume and track manufacturing operations. Use this tool with table ID to retrieve record counts for analysis and reporting.

Instructions

Counts records in a Tulip Table. Corresponds to GET /tables/{tableId}/count. Requires tables:read scope. [READ-ONLY]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableIdYesThe ID of the table to count records in
Behavior4/5

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 effectively communicates key traits: it's a read-only operation (explicitly marked '[READ-ONLY]'), requires specific permissions ('tables:read' scope), and corresponds to a specific API endpoint. It doesn't mention rate limits or error conditions, but covers the essential safety and access profile.

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 extremely concise (just two sentences) and front-loaded with the core purpose. Every element earns its place: the action, resource, API correspondence, permission requirement, and read-only designation all serve distinct purposes without redundancy or fluff.

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

Completeness4/5

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

For a simple read operation with one parameter and no output schema, the description is reasonably complete. It covers purpose, permissions, and behavioral safety. However, without an output schema, it doesn't describe what the count returns (e.g., integer format, error responses), leaving some ambiguity about the result structure.

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?

The input schema has 100% description coverage, with the single parameter 'tableId' clearly documented in the schema. The description doesn't add any additional parameter meaning beyond what the schema already provides (e.g., no examples of table IDs or format requirements), so it meets the baseline for high schema coverage.

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 specific action ('Counts records') and resource ('in a Tulip Table'), distinguishing it from sibling tools like listTableRecords (which lists records) or getTable (which retrieves table metadata). The verb+resource combination is precise and unambiguous.

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

Usage Guidelines4/5

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

The description provides clear context by mentioning the required scope ('tables:read'), which helps determine when this tool can be used. However, it doesn't explicitly differentiate when to use this versus alternatives like listTableRecords (which might provide more detailed record information) or getTableAggregation (which might perform other calculations).

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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