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abdul-hamid-achik

Tarot MCP Server

perform_reading

Generate tarot card readings using specific spreads like Celtic Cross or Past-Present-Future to provide insights and guidance based on user questions.

Instructions

Perform a tarot reading with a specific spread

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
spreadIdYesID of the spread to use (e.g., "celtic-cross", "past-present-future")
questionNoOptional question for the reading
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states what the tool does but doesn't disclose whether it's read-only or mutative (though 'perform' suggests action), what the output format might be (text, structured data), error conditions, or any rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.

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, focused sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action ('perform a tarot reading') and efficiently specifies the key constraint ('with a specific spread'). Every element earns its place, making it easy to parse quickly.

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?

Given the complexity of performing a tarot reading (which likely involves card selection, interpretation, and structured output), the description is inadequate. With no annotations, no output schema, and minimal behavioral details, it fails to convey what the tool actually returns or how it behaves. Siblings like 'interpret_reading' suggest this might be part of a workflow, but the description doesn't clarify that relationship.

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%, with both parameters clearly documented in the schema: 'spreadId' specifies example values and 'question' is noted as optional. The description adds no additional parameter semantics beyond implying that 'spreadId' is required for execution. This meets the baseline for high schema coverage but doesn't enhance understanding.

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 action ('perform a tarot reading') and specifies the resource ('with a specific spread'), making the purpose immediately understandable. It distinguishes from siblings like 'daily_card' (single card) and 'draw_cards' (generic drawing) by emphasizing the structured spread aspect. However, it doesn't explicitly differentiate from 'interpret_reading', which might be a follow-up analysis tool.

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. It doesn't mention prerequisites (e.g., needing a spread ID from 'list_spreads'), when to choose it over 'draw_cards' for simpler readings, or how it relates to 'interpret_reading' for post-processing. The agent must infer usage from context alone.

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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