Skip to main content
Glama
astroway-mcp

astroway-mcp

Official
by astroway

Dashas: Tribhagi Pranadasha

astroway_vedic_dashas_tribhagi_prana
Read-onlyIdempotent

Computes the Tribhagi Pranadasha, a five-level Vedic dasha cascade down to the finest grain, from a natal chart's birth data and an optional target date and time.

Instructions

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

[Group: Vedic] [Endpoint: POST /v1/vedic/dashas/tribhagi/prana] [Cost: 20 credits (Tier 2)]

Input 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.

Output Schema

NameRequiredDescriptionDefault
levelNo
systemNo
initialNo
periodsNo
ayanamsaNo
nakshatraNo
currentMahaNo
currentAntarNo
currentSookshmaNo
currentPratyantarNo
moonSiderealLongitudeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.6.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so safety is covered. The description adds two genuinely useful behavioral facts not in annotations: the 20-credit (Tier 2) cost and the POST endpoint. However it says nothing about what the response contains (period lords, start/end dates, number of rows) or whether birth data is the only input.

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?

Front-loaded with the system name and the discriminating detail ('finest grain'), followed by structured metadata lines for group, endpoint and cost. No wasted prose, though the bracketed lines are boilerplate rather than explanation.

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?

For a 20-credit compute endpoint the description is thin: it never says this returns a time-ordered dasha table for a natal chart, nor that targetDate/targetTime optionally shift the period window. Rich schema and an output schema cover the mechanics, but the conceptual output is left to domain knowledge.

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% and the body schema documents birth data, timezone handling, ayanamsa and house system in detail, so the schema does the heavy lifting. The description contributes nothing about parameters, which is the baseline-3 case rather than a value-add.

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 (Tribhagi Pranadasha) and characterizes the level as a '5-level cascade (finest grain)', which distinguishes it from the sibling tribhagi_maha/antar/pratyantar/sookshma tools. It lacks an explicit verb ('compute/return'), so the purpose reads as a label rather than a full statement, but the level differentiation is real.

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?

No explicit when-to-use or when-not-to-use guidance, and no sibling is named as an alternative. The phrase 'finest grain' implicitly signals that this is the most granular of the Tribhagi levels, so an agent can infer selection from granularity, but only by inference.

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

Deploy Server

Other Tools