Astroguru Report is a Vedic astrology skill that takes natural-language birth details and produces comprehensive, deterministic astrological reports. It runs a local, standalone calculation engine rather than relying on prompting, so the astrological data it generates is consistent and reproducible across runs.

The skill handles geocoding of birth locations, normalizes timezones to Indian Standard Time (IST), and computes Vimsottari Dasha (predictive timing) sequences alongside Gochara (transit) analysis. From those calculations it produces a structured report that includes goal-oriented outlooks with broad timeframes, practical recommendations, and optional spiritual practices.

Output can take two forms: a plain CLI summary suitable for conversational agent responses, or a persisted animated HTML report that can be delivered as a file artifact. The calculation scripts themselves do not call any LLM provider; the active agent handles narrative interpretation of the structured data the skill returns.

Setup involves unzipping the skill folder into an agent’s skills or workspace directory, then creating a local Python environment by following SETUP.md and installing dependencies from requirements.txt. Python 3.10 or 3.11 is recommended. This skill is appropriate when an agent workflow needs reliable, structured Vedic chart data without delegating astronomical computation to a language model.

Use cases

Generate a full Vimsottari Dasha timeline from a user's name, birth date, birth time, and birth city

Produce an animated HTML astrology report artifact that can be saved and shared

Normalize a birth location and time to IST for accurate Vedic chart computation

Add Gochara (planetary transit) analysis to an agent's response about a user's near-term outlook

Embed structured astrological data into a larger agent workflow that handles its own interpretation

When to use it

When an agent needs deterministic, locally computed Vedic astrology data rather than LLM-guessed charts

When the deliverable should be a persisted animated HTML report file

When Vimsottari Dasha timing or Gochara transit analysis is required

When geocoding and IST timezone normalization must be handled automatically from natural-language input

When not to use it

When Western astrology systems such as the tropical zodiac are needed instead of Vedic

When no local Python 3.10 or 3.11 environment can be set up in the agent's workspace

When the deployment environment prohibits installing dependencies from a requirements.txt file

When the use case requires real-time LLM-generated interpretation rather than structured data passed back to an agent