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Glama
Dinesh-Gahlot

mcp-indian-astrology

divine_get_ashtakvarga

Read-onlyIdempotent

Generate Bhinnashtakvarga tables for each planet, showing benefic dot strengths across signs. Analyze sign strength and predict transits using the 8x12 Ashtakvarga grid.

Instructions

Get Bhinnashtakvarga (individual Ashtakvarga) tables for all planets.

Returns the 8x12 benefic dots table for each planet showing strength in each sign. Used for transit prediction and sign strength analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.9.1

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already cover readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is established. The description adds the output format (8x12 table per planet) and purpose, which is useful but does not disclose other behavioral traits like error handling or data requirements. Given the annotation coverage, this is adequate but not extensive.

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 two sentences, front-loaded with the primary action and output, and every sentence adds value. There is no fluff or repetition.

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 the tool's complexity (requires full birth details), the description explains the core functionality and output, and the schema covers the input parameters. With an output schema present, return values are not needed. It could be slightly more explicit about the need for birth details, but the schema provides that. Overall, it is reasonably complete.

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?

The tool description contains no parameter information, and schema description coverage is 0%. The schema itself has detailed descriptions for each birth detail field, but the description does not compensate for the low coverage by explaining that birth details are required or how they relate to the tool. The agent must rely solely on the schema, which is adequate but the description offers no additional semantic help.

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?

The description clearly states it retrieves Bhinnashtakvarga (individual Ashtakvarga) tables for all planets, specifies the output as 8x12 benefic dot tables, and notes its use for transit prediction and sign strength analysis. This is a specific verb-resource pair and distinguishes it from the sibling divine_get_sarvashtakavarga, which would handle total Ashtakvarga.

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 description provides clear usage context ('Used for transit prediction and sign strength analysis') and implicitly differentiates from other tools by focusing on individual Ashtakvarga. However, it does not explicitly mention when not to use it or name alternative tools like sarvashtakavarga, so it lacks explicit exclusions.

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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