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Relationship compatibility (business, friends, siblings, and more)

calculate_relationship_compatibility
Read-onlyIdempotent

Gender-neutral Nakshatra compatibility between any two people for a chosen bond — business partner, friend, sibling, colleague, mentor/student, roommate or general. Resolves both places, calculates both charts, and returns per-factor Tara, Graha Maitri, Gana, Yoni, Bhakoot and Moon-element evidence weighted for that relationship, plus a 0-100 harmony index. Traditional research preview; never a verdict on any relationship.

Input Schema

NameRequiredDescriptionDefault
personAYes
personBYes
languageNoen
relationshipYesgeneral

Output Schema

NameRequiredDescriptionDefault
safetyYes
factorsYes
harmonyYes
subjectsYes
relationshipYes
schemaVersionYes
sourceCoverageYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / personA / required
      Previous value: -[
      -  "name",
      -  "date",
      -  "time"
      -]New value: +[
      +  "date",
      +  "time"
      +]
    • changedInput schema / properties / personB / required
      Previous value: -[
      -  "name",
      -  "date",
      -  "time"
      -]New value: +[
      +  "date",
      +  "time"
      +]
  2. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so safety is covered. The description adds genuine behavioral context: it resolves both places, computes both charts, and returns weighted per-factor evidence and a 0-100 index, plus an epistemic disclaimer. Good value beyond the structured fields.

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?

Three sentences, front-loaded with purpose, then mechanism/output, then caveat. Dense but every clause carries information; no filler.

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?

An output schema exists, so return values need not be explained, yet the description usefully summarizes them. For a nested-object tool the description is largely complete, falling short only on inner person parameters that the schema itself leaves undocumented.

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 0% and there are nested person objects at 4 params. The description lists the relationship options (matching the enum) and notes both places are resolved, adding some meaning, but it says nothing about the personA/personB structure, timezone/timezoneOffset, or language.

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?

States a specific verb+resource (calculate Nakshatra compatibility between two people) plus the scope (non-romantic bonds: business partner, friend, sibling, colleague, mentor/student, roommate, general). This enumeration implicitly separates it from the sibling calculate_compatibility (romantic/marriage) without ambiguity.

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

Usage Guidelines4/5

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

The enumerated bond types give clear context for when to invoke it, and the closing caveat frames it as a research preview. However, it never names an alternative (e.g. calculate_compatibility) or states when NOT to use it, so routing is inferred rather than explicit.

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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