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

Sahams (Arabic Parts)

get_sahams
Read-onlyIdempotent

Return the sahams (Arabic parts / sensitive points) of the chart. The result maps each saham name to its computed zodiacal position, formatted as sign + degrees, minutes and seconds (e.g. 'Gemini 28° 47’ 58"'). Includes the full set such as Punya, Vidya, Yasas, Mitra, Vivaha, Putra, Karma, Roga, Mrithyu and the rest. Data only — no interpretation is added.

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

A3.6/5.0
Behavior4/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, so the bar is lower. The description adds genuinely useful behavioral context: the exact return format (sign + degrees/minutes/seconds), coverage of the full set of sahams, and the guarantee that no interpretation is included. This goes beyond the annotations without contradicting them.

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 compact and well-structured. The first sentence states the action and resource, the second clarifies the output format with a concrete example, and the third sets expectations about interpretation. Every sentence earns its place with no redundancy.

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 that there is no output schema, the description does a good job of defining the return shape and scope. It explains the result format, the set of sahams, and the data-only nature. Minor omissions like error behavior or handling of invalid birth data are not significant given the strong schema coverage and read-only annotations.

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?

Schema description coverage is 100%, so the baseline of 3 applies. The description does not add parameter-level detail, but the schema already documents each parameter sufficiently, so no compensation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Return the sahams') and clearly describes the output as a mapping of saham names to zodiacal positions, with examples. It is clear what the tool does, though it does not explicitly differentiate itself from sibling tools like get_sphutas or get_yogas.

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

Usage Guidelines2/5

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

No explicit guidance is given about when to prefer this tool over alternatives. The note that it returns 'data only — no interpretation' hints at a limitation, but it does not name sibling alternatives or state conditions for selection, leaving usage mostly to inference.

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