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Jagannatha Hora — Vedic Astrology (Jyotish, Kundli, Horoscope, Panchang)

Doshas

get_doshas
Read-onlyIdempotent

Return the standard dosha (planetary affliction) checks for the chart. The result maps each dosha name to a verdict describing whether it is present in this horoscope and the reasoning. Doshas covered: Kala Sarpa Dosha, Manglik Dosha, Pitru Dosha, Guru Chandala Dosha, Ganda Moola Dosha, Kalathra Dosha, Ghata Dosha and Shrapit Dosha. The verdict text may contain light HTML markup (e.g. ). Data only — no interpretation is added beyond what the engine reports.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesBirth date in YYYY-MM-DD format, e.g. 1985-06-15
timeYesBirth time in 24h HH:MM:SS format, e.g. 10:30:00
placeNoOptional birth-place name (cosmetic only).
genderNoOptional. A few classical yogas are defined by gender -- Mahabhagya's rule is gender x day/night x odd/even signs. Supply it when known; when omitted those yogas are left out of the result rather than computed against an assumed gender.
latitudeYesBirth-place latitude in decimal degrees, e.g. 13.0827
timezoneYesTimezone offset from UTC in hours, e.g. 5.5 for IST
longitudeYesBirth-place longitude in decimal degrees, e.g. 80.2707

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds genuinely useful behavioral context beyond those annotations: the result is a mapping of dosha name to verdict and reasoning, the verdict text may include light HTML markup, and no interpretation is added beyond the engine's report. This sets clear expectations for a tool with no output schema.

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 first sentence front-loads the action and result, the dosha list is compact but complete, and the HTML and data-only caveats are each one short sentence. Every sentence contributes useful information with no filler.

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?

With no output schema, the description carries the burden of explaining the return shape and content, and it does so clearly: a map of dosha names to presence verdicts and reasoning, with possible HTML and no added interpretation. Input context is fully handled by the high-coverage schema, so nothing essential is missing for an agent to invoke this tool correctly.

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?

The input schema has 100% parameter description coverage, so the structured data already explains all parameters. The description adds no parameter-specific semantics beyond saying they define the chart, so the baseline score of 3 is appropriate.

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 states a specific verb and resource: 'Return the standard dosha (planetary affliction) checks for the chart.' It further lists every dosha covered, so an agent unambiguously knows what this tool does and can distinguish it from sibling tools like get_yogas or get_planetary_states.

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

Usage Guidelines3/5

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

Usage is implied rather than explicit: the description implies the tool is for computing dosha verdicts, and the data-only note narrows interpretation. However, it never states when to prefer this over alternatives or when not to use it, nor does it name any sibling tool.

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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TDQS

A3.8/5.0
Disambiguation3/5

Many tools form near-identical families—bala strengths (get_shad_bala, get_bhava_bala, get_other_bala, get_vaiseshikamsa_bala, get_vimsopaka_bala), arudhas (get_arudha_padas, get_graha_arudhas, get_chandra_arudhas, get_surya_arudhas), and transit snapshots (get_gochara, get_gochara_range, get_saturn_transit, get_muhurta). The detailed descriptions usually clarify, but an agent without deep Jyotish knowledge could easily select the wrong one, especially for vaiseshikamsa vs vimsopaka bala.

Naming Consistency4/5

The vast majority of tools use a clean get_<topic> snake_case pattern, such as get_dasha, get_muhurta, and get_yogas. The two outliers—generate_horoscope and list_divisional_charts—are still readable verb-noun names, so the inconsistency is minor.

Tool Count2/5

32 tools is above the 25+ threshold for too many. Many tools are variations on the same chart computations and could be consolidated into parameterized tools, such as a single bala strength tool with a bala_type argument. The high count will make tool selection harder for agents despite each tool covering a legitimate niche.

Completeness5/5

The surface is remarkably complete for Vedic astrology: chart generation, divisional charts, nakshatras, all major strength systems, dasha timelines, transits, muhurta, yogas, doshas, marriage matching, and specialized points are all present. There are no obvious dead ends for the core workflow of generating and analyzing a horoscope.

Resources