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pietrodileo

IRIS MCP Blueprint

by pietrodileo

start_production

Start an existing InterSystems IRIS interoperability production by providing its class name. Use after creating or deploying the production class.

Instructions

Start an Interoperability production by class name (must already exist and be compiled).

Calls ##class(Ens.Director).StartProduction(productionName) (single-argument form compatible with the IRIS Native SDK and servers where the two-argument sync overload is not exposed to Python). It does not create the production class; use create_empty_production or deploy a class from source, then call this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
production_class_nameYesFull production class name (e.g. `MCPTest.EmptyProduction`).
synchronousNoReserved for future use; start mode follows the server's single-arg API.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description must cover behavioral traits. It mentions the specific API call and compatibility notes, but does not disclose side effects, error conditions, or authentication requirements.

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?

Description is three sentences, front-loaded with main action, no extraneous words, well-structured.

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?

Given no annotations and presence of output schema, description covers prerequisites, API call, and distinguishes from creation tools. Could mention return values or error handling, but overall adequate.

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 has 100% coverage; description adds minimal extra info about synchronous parameter being reserved and the single-argument API, but does not elaborate on parameter semantics beyond schema.

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?

Description clearly states verb 'Start' and resource 'Interoperability production by class name', and differentiates from tools that create productions (e.g., create_empty_production).

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

Usage Guidelines5/5

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

Explicitly states prerequisite (must exist and be compiled) and what it does NOT do (create the class), directing users to alternatives like create_empty_production or deploy from source.

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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