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ephemeris_synastry

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Calculate synastry charts comparing two people's natal charts. Returns inter-aspects (planetary connections between two charts), composite points, and relationship indicators. Use for compatibility analysis, relationship timing, or partnership insights.

Instructions

Calculate a synastry chart comparing two people's natal charts. Returns inter-aspects (planetary connections between the two charts), composite points, and relationship indicators. Use this for compatibility analysis, relationship timing, or partnership insights.

CREDIT COST: 3 credits per call.

EXAMPLE: Compare two people's charts: person_a_datetime='1990-04-15T14:30:00', person_a_latitude=41.8781, person_a_longitude=-87.6298, person_b_datetime='1988-09-22T08:15:00', person_b_latitude=34.0522, person_b_longitude=-118.2437

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
person_a_datetimeYesPerson A birth datetime (ISO 8601).
person_a_latitudeYesPerson A birth latitude.
person_a_longitudeYesPerson A birth longitude.
person_b_datetimeYesPerson B birth datetime (ISO 8601).
person_b_latitudeYesPerson B birth latitude.
person_b_longitudeYesPerson B birth longitude.
house_systemNoHouse system for both charts. Defaults to 'placidus'.
formatNoOutput format. 'llm' is compact and token-efficient (available on all tiers).
include_visualNoWhen true, renders a bi-wheel SVG comparing both charts and embeds it in the response. The chart image will display in the conversation alongside the data. Costs 2 additional credits on top of the base call cost.
visual_configNoOptional rendering preferences (only used when include_visual=true).
Behavior4/5

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

Annotations readOnlyHint=true and destructiveHint=false already indicate safe behavior. Description adds credit cost and visual option cost details, enhancing transparency without contradiction.

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?

Description is concise, front-loaded with purpose, includes example and credit cost. No wasted words, well-structured.

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?

Given 10 parameters, 6 required, no output schema, description covers returns (inter-aspects, composite points, indicators) and provides example. Lacks details on pagination or limits, but overall sufficient.

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

Parameters4/5

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

Input schema has 100% description coverage, so baseline is 3. Description adds value with a concrete example and credit cost, slightly improving semantics. Nested visual_config is also described.

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?

Description clearly states the tool calculates a synastry chart comparing two natal charts, including inter-aspects, composite points, and relationship indicators. It distinguishes from siblings by specifying its purpose for compatibility analysis.

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?

Provides explicit use cases: compatibility analysis, relationship timing, partnership insights. Does not explicitly state when not to use or list alternatives, but context signals many sibling tools, making differentiation implicit.

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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