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by com.asterwise.mcp
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Moon Sign Horoscope

asterwise_get_horoscope
Read-onlyIdempotent

Fetches an AI-synthesised Moon-sign horoscope for a chosen horizon and returns structured guidance fields plus metadata about the model and period.

WORKFLOW: BEFORE: None — this tool is standalone. AFTER: asterwise_get_natal_chart — if the user needs a personalised chart beyond sign-general copy.

INPUT CONTRACT: period is constrained to the tool schema enum (daily, weekly, monthly, yearly). moon_sign accepts Sanskrit (Tula, Vrischika, Karka, Simha, Kanya, Dhanu, Makara, Kumbha, Meena, Mesha, Vrishabha, Mithuna) or English (Libra, Scorpio, Cancer, Leo, Virgo, Sagittarius, Capricorn, Aquarius, Pisces, Aries, Taurus, Gemini); resolution is upstream. response_format selects JSON vs markdown rendering only.

DO NOT CONFUSE WITH: asterwise_get_natal_chart — full personalised sidereal chart from birth data, not Moon-sign editorial copy. asterwise_get_gochar — nine-planet transit snapshot vs natal chart for today, not AI horoscope prose.

Full output and error contract: https://docs.asterwise.com/mcp/tools/get-horoscope/

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodYesHoroscope period: daily, weekly, monthly or yearly.
moon_signYesVedic moon sign (rashi), e.g. 'Vrishabha' or 'Taurus'.
response_formatNoOutput format: 'markdown' (default) for a readable report, or 'json' for the raw structured payload.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / moon_sign / description
      Added value: +"Vedic moon sign (rashi), e.g. 'Vrishabha' or 'Taurus'."
    • addedInput schema / properties / period / description
      Added value: +"Horoscope period: daily, weekly, monthly or yearly."
    • addedInput schema / properties / response_format / description
      Added value: +"Output format: 'markdown' (default) for a readable report, or 'json' for the raw structured payload."
  2. Changed2 schema fields changed
    • addedInput schema / properties / response_format / default
      Added value: +"markdown"
    • changedInput schema / required
      Previous value: -[
-  "moon_sign",
-  "period",
-  "response_format"
-]New value: +[
+  "moon_sign",
+  "period"
+]
  3. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior; the description adds that this is an AI-synthesised editorial horoscope, returns structured guidance fields plus model/period metadata, and that response_format only controls rendering between markdown and JSON. It also references a full output/error contract URL, providing meaningful behavior beyond the annotations.

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 longer than minimal, but every section earns its place: purpose, workflow, input contract, disambiguation, and documentation link. The structure is clear and front-loaded with the core purpose before supporting details, making it efficient despite its length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists, the description appropriately focuses on selection, input constraints, disambiguation, and the contract URL for full output/error details. It covers before/after workflow and alternatives, so an agent has everything necessary to invoke the tool correctly in context.

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?

Schema coverage is 100%, so the baseline is already strong, but the description adds genuine value by expanding moon_sign to include Sanskrit and English rashi names, clarifying that period is constrained to the schema enum, and specifying that response_format only selects rendering mode. This helps an agent understand valid inputs beyond the basic schema descriptions.

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 clear, specific action: fetches an AI-synthesised Moon-sign horoscope for a chosen horizon, and distinguishes the resource and deliverable from sibling tools. The 'DO NOT CONFUSE WITH' section explicitly contrasts it with asterwise_get_natal_chart and asterwise_get_gochar, so an agent can select it correctly.

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

Usage Guidelines5/5

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

Provides explicit when-to-use guidance via WORKFLOW and DO NOT CONFUSE sections, naming the exact sibling tools and their purposes. It also notes that a personalized chart should use asterwise_get_natal_chart, giving clear exclusion criteria.

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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