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ClueoFoundation

OpenClueo MCP Server

simulate_response

Generate AI responses with customizable Big Five personality traits to test behavioral consistency across platforms.

Instructions

Simulate an AI response with specific personality traits

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe prompt to respond to
personalityYesBig Five personality dimensions (1-10 scale)
apiKeyNoOptional Clueo API key for authentication
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description mentions 'simulate' but doesn't clarify what that means operationally: whether this is a read-only simulation, if it has side effects, what authentication is required (though the schema shows an optional apiKey), or what the output format might be. For a tool with no annotations, this leaves significant behavioral questions unanswered.

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, efficient sentence that clearly states the tool's core function. There's no wasted verbiage, and it's appropriately front-loaded with the essential information.

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

Completeness2/5

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

For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'simulate' means in practice, what the output looks like, or how this differs from related sibling tools. Given the complexity implied by personality trait parameters and the lack of structured behavioral information, the description should provide more context about the tool's operation and results.

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's in the schema. The baseline of 3 is appropriate when the schema does all the parameter documentation work.

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 tool's purpose: 'Simulate an AI response with specific personality traits'. It specifies the verb ('simulate') and resource ('AI response'), and mentions the key feature ('specific personality traits'). However, it doesn't differentiate from sibling tools like 'inject_personality' or 'inject_preset_personality', which appear related to personality manipulation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'inject_personality' and 'inject_preset_personality' that seem related to personality traits, there's no indication of when this simulation tool is preferred over those injection tools or other siblings.

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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