Skip to main content
Glama

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

Aṣṭakavarga

get_ashtakavarga
Read-onlyIdempotent

Return the Ashtakavarga bindu (benefic point) scores for the chart, labelled by planet and sign. 'binna_ashtaka_varga' (BAV) maps each of the Sun, Moon, Mars, Mercury, Jupiter, Venus, Saturn and the Ascendant to its bindu count in every sign (Aries..Pisces, 0-8 each). 'samudhaya_ashtaka_varga' (SAV) is the combined total per sign across the seven planets (sums to 337); higher SAV signs are stronger. 'sodhita_ashtaka_varga' (SoAV) is that same BAV after Trikona and Ekaadhipatya sodhana — the reduced grid the pindas are actually computed from — keyed by planet Sun..Saturn (7 rows; the Ascendant has no reduced row). 'raasi_pindas', 'graha_pindas' and 'sodhya_pindas' give per-planet pinda totals (sodhya = raasi + graha), keyed by planet Sun..Saturn. Data only — no interpretation is added. (The detailed prastara contributor grid is not included.)

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

A4.5/5.0
Behavior5/5

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

Annotations already declare read-only and idempotent, and the description adds substantial internal behavior: it explains what BAV, SAV, and SoAV mean, that SoAV is computed via Trikona and Ekaadhipatya sodhana, that SAV sums to 337, and that pindas derive from the reduced grid. It also explicitly notes the prastara grid is not included. This goes well beyond the annotation baseline.

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 dense but every clause contributes: it front-loads the core return statement and then explains each output field, row counts, summation behavior, and exclusions. No filler or redundant repetition; the details are structured and necessary for correct use. This is appropriately sized for a complex, output-schema-less tool.

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?

Since there is no output schema, the description carries the full burden of documenting the return value. It does so thoroughly: every key is defined, row counts are explicit, the meaning of SAV totals and SoAV is explained, and the relationship between pindas is clarified. Combined with the schema, an agent has everything needed to invoke and interpret the 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 already provides descriptions for all 7 parameters (100% coverage), including formats and examples, so the baseline is 3. The tool description adds parameter-specific meaning only through the term 'data only', but it correctly relies on the schema for parameter documentation. No parameter information is missing.

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 opens with a specific verb ('Return'), names the exact resource (Ashtakavarga bindu scores), and labels results by planet and sign. It then enumerates every output field (BAV, SAV, SoAV, pindas), which fully distinguishes it from the many sibling yaga/dosha tools. This is a clear statement of what the tool does and what it returns.

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 states the data-only scope ('Data only — no interpretation is added') and explicitly excludes the prastara contributor grid, giving an agent clear boundaries for when this tool is relevant. It does not name sibling alternatives, but the stated exclusions and scope make the intended use case evident. This is clear context with exclusions, though not a full when-to-use routing guide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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