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Memory Alpha MCP Server

holodeck_program

Generate a Star Trek holodeck program designation, assess safety protocols, and estimate malfunction probability from your scenario.

Instructions

Generate a Star Trek holodeck program designation, safety assessment, and malfunction probability

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scenarioYesDescribe the desired holodeck scenario (e.g. "A noir detective mystery in 1940s San Francisco")
safety_protocolsNoWhether safety protocols are enabled (default: true)
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does state that the tool generates three artifacts (designation, safety assessment, malfunction probability), which is useful. However, it omits details such as whether output is text vs. structured data, how the safety_protocols parameter influences behavior, and any edge cases or limitations.

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, front-loaded sentence that conveys the core function and outputs without any filler. Every word contributes meaning, and it is properly sized for the tool's simplicity.

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 generation tool with rich schema coverage and no output schema, the description lists the output components, covering return-value expectations. It does not specify formatting or response structure, but that is not critical for a creative generation tool and the context is otherwise complete.

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%, and both parameters are clearly described in the schema (scenario with an example, safety_protocols with default). The description itself adds no parameter-specific meaning beyond confirming the generation scope, so it meets the baseline but does not exceed it.

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 specifies a clear verb ('Generate'), a distinct resource ('Star Trek holodeck program'), and three concrete outputs (designation, safety assessment, malfunction probability). This distinguishes it from sibling tools like episode_recommender or diplomatic_scenario, which serve different creative or reference functions.

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 the tool is used when a user wants a holodeck program, but it does not explicitly state when to use it versus alternatives, nor does it mention any exclusions or prerequisites. The context is clear but not framed as guidance.

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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