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@prismicio/mcp-server

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by prismicio

how_to_mock_slice

Generate a validated slice mock (mocks.json) covering all variations, with guidance for text-only refinements based on user intent.

Instructions

PURPOSE: Generate a model-valid slice mock (mocks.json) and provide guidance for text-only refinements.

USAGE: Use when creating or updating slice mocks.

RETURNS: A JSON mock covering all variations, plus guidance for text-only refinements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sliceMachineConfigAbsolutePathYesAbsolute path to 'slicemachine.config.json' file
sliceDirectoryAbsolutePathYesAbsolute path to the slice directory (contains model.json)
userIntentYesUser-provided guidance describing desired mock changes, tone, quantities, constraints
Behavior3/5

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

No annotations are provided, so the description must disclose behavior. It states it 'generate[s]' a mock and 'provide[s] guidance,' but it doesn't clarify if this is a read-only operation or if it modifies files. It also doesn't mention permissions or side effects. It's adequate but lacks depth.

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 concise with three clear sections: PURPOSE, USAGE, RETURNS. Every sentence adds value without repetition. It is front-loaded with the purpose. Slightly more detail could be added without being verbose, so not a perfect 5.

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 tool has 3 parameters, no output schema, and no annotations, the description covers the basic purpose but lacks completeness. It doesn't clarify whether the tool reads/writes files, the format of the returned JSON, or how it relates to sibling tools. More detail would be needed for full context.

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% coverage with clear descriptions for each parameter (e.g., absolute paths, user intent). The tool description does not add extra meaning beyond what the schema already provides, but the schema itself is sufficient. Following the baseline rule for high coverage, a score of 3 is appropriate.

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 tool's purpose: 'Generate a model-valid slice mock (mocks.json) and provide guidance for text-only refinements.' The verb 'generate' and resource 'slice mock' are specific. The sibling tools include other how-to tools (code, model), so this tool is distinct as the mocking one.

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 says 'Use when creating or updating slice mocks.' This gives a clear context but does not explicitly mention when not to use it or provide alternative sibling tools. No exclusions or comparisons are given, so it's implied but not fully guided.

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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