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Lenormand: Relationship

astroway_tarot_lenormand_draw_relationship
Read-onlyIdempotent

7-card relationship dynamics.

[Group: Tarot: Lenormand] [Endpoint: POST /v1/tarot/lenormand/draw/relationship] [Cost: 10 credits (Tier 1)]

Input Schema

NameRequiredDescriptionDefault
artNoCard art set, e.g. rws-1909, rws-restored, rws-vector. GET /v1/tarot/decks lists the sets per deck.
seedNo
fieldsNoCompact mode: comma-separated dotted paths to keep, relative to `data`, e.g. "planets.name,planets.longitude,houses.cusp". Omit for the whole response.
questionNo
precisionNoCompact mode: round fractional numbers to this many decimals. Longitudes carry 14 by default; 2 is finer than any chart is drawn.
allowReversedNo

Output Schema

NameRequiredDescriptionDefault
seedNo
drawnNo
spreadNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / art
      Added value: +{
      +  "description": "Card art set, e.g. rws-1909, rws-restored, rws-vector. GET /v1/tarot/decks lists the sets per deck.",
      +  "maxLength": 40,
      +  "type": "string"
      +}
  2. First observed

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world, so the safety profile is covered. The description adds genuinely useful behavioral context in the cost (10 credits, Tier 1) and the concrete endpoint, but says nothing about latency, deck requirements, or how randomness/seed behaves.

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?

Extremely short and front-loaded — the spread definition leads, with group/endpoint/cost as bracketed metadata. Nothing is padded, though the metadata lines are boilerplate rather than tool-specific explanation.

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?

An output schema exists, so return values need not be described, and annotations handle safety. What remains missing is routing guidance among the many Lenormand/tarot draws and any note on the optional question parameter, leaving the definition adequate but thin for a spread-selecting tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50% across 6 parameters, and the description contributes nothing about art, seed, fields, question, precision or allowReversed. With half the parameters undocumented and no descriptive compensation, the agent has no extra semantic grounding.

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?

States a specific verb+resource+scope: a 7-card Lenormand draw for relationship dynamics. The spread size and topic distinguish it from Lenormand siblings such as the three-card, nine-card square, line of five and grand tableau, though it never names them explicitly.

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?

There is no guidance on when to choose this spread over the other Lenormand draws (three_card, line_of_five, 9_card_square, grand_tableau, celtic_cross_lenormand) or over the Rider-Waite relationship draw. The agent must infer selection purely from spread size.

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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