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AstroWay Astrology API (full catalogue)

Dashas: Shoola Pranadasha

astroway_vedic_dashas_shoola_prana
Read-onlyIdempotent

Shoola Pranadasha: 5-level cascade (finest grain).

[Group: Vedic] [Cost: 20 credits (Tier 2)]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesBirth data for a single natal chart. Required: date (YYYY-MM-DD), time (HH:mm:ss), latitude and longitude in decimal degrees. The short forms lat, lon, lng and tz are rejected with 400 INVALID_FIELD; pass the full names. timezoneOffset is hours from UTC and defaults to 0, meaning UTC; send timezone instead (an IANA name such as Europe/Kyiv, or auto) and the offset for that date is worked out, summer time included. city is a display label only: nothing here geocodes it, so it never stands in for coordinates. houseSystem is a single Swiss Ephemeris letter, P by default; a name such as "Placidus" is refused, and the case matters because I and i are two different Sunshine systems.
fieldsNoCompact mode: comma-separated dotted paths to keep, relative to `data`, e.g. "planets.name,planets.longitude,houses.cusp". Omit for the whole response.
precisionNoCompact mode: round fractional numbers to this many decimals. Longitudes carry 14 by default; 2 is finer than any chart is drawn.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
lagnaNo
levelNo
systemNo
periodsNo
ayanamsaNo
currentMahaNo
currentAntarNo
currentSookshmaNo
currentPratyantarNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new operational context not in the annotations — the 20-credit Tier 2 cost — plus the cascade depth. It says nothing about output shape or timing, but the output schema exists, so this is adequate rather than rich.

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?

Two lines plus bracketed Group/Cost metadata, front-loaded with the dasha name and depth descriptor. No filler, though the brevity borders on under-specification for a cost-bearing calculation tool.

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

Completeness3/5

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

The schema and output schema carry the structural burden, and the cost tag covers pricing, but against a sibling set of hundreds of dasha tools the description does not distinguish Shoola from other systems (ashtottari, chara, kalachakra, etc.) or explain what the five cascade levels represent. It is minimally sufficient, not complete.

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%, with the nested birth-data object, fields, and precision all thoroughly documented in the schema itself. The description contributes nothing about parameters, which is acceptable at full coverage, so the baseline 3 applies.

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?

Names the specific dasha system and level (Shoola Pranadasha) and characterizes it as a '5-level cascade (finest grain)', which lets an agent place it among the shoola_maha/antar/pratyantar/sookshma siblings by depth. It lacks an explicit verb ('compute/calculate') and never names the siblings directly, so differentiation is inferred rather than stated.

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?

The 'finest grain' comparative cue implies when to pick this over the shallower shoola levels, but there is no explicit when-to-use, when-not-to-use, or named alternative. The agent must infer the selection rule from the level-depth wording alone.

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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