Kaalshodh — Indian astronomy time machine

get_planetary_positions

Read-only

Return the rashi (zodiac sign) and retrograde status of the 9 grahas at
any instant in years -5000..+5000, plus the paksha (lunar fortnight).

Served from precomputed lookup tables — O(log n), instant even for
"where was Shani on this day in 3102 BCE?".

Example questions: "which planets are retrograde right now?",
"what sign was Guru in when I was born?", "sky snapshot for 500 CE".

Args:
    time:      ISO 8601 UTC datetime (e.g. "2026-03-22T12:00:00Z").
               Negative years allowed (e.g. "-3101-02-18T00:00:00Z").
               Defaults to now.
    ayanamsa:  "Lahiri" (Vedic sidereal, default) or "Sayan" (tropical).
    grah:      Optional single planet (Surya, Chandra, Mangala, Budha,
               Guru, Shukra, Shani, Rahu, Ketu) — returns just that one.

Returns:
    Dict with time, ayanamsa, paksha (Shukla/Krishna), and grahas mapping
    each planet to its rashi name and retrograde status (or the single
    grah's status when `grah` is given).

Input Schema

TableJSON Schema

Name	Required	Default
`grah`	No
`time`	No
`ayanamsa`	No	Lahiri

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already provide readOnlyHint=true, and the description adds useful behavioral context: data is served from precomputed lookup tables with O(log n) performance, and it handles a wide historical range. 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 well-structured with a clear intro, a performance note, example questions, Args section, and Returns section. Every sentence adds value and there is no fluff. It is appropriately sized for the tool's complexity.

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?

Given no output schema, the description explicitly states the return format (a dict with time, ayanamsa, paksha, and grahas mapping). It also covers parameter details and usage examples, providing a complete picture for the agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description compensates fully. It explains each parameter: time format (ISO 8601, negative years, default now), ayanamsa options with defaults, and the optional grah parameter with a list of possible planet names and behavior. This adds substantial meaning beyond the bare schema.

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 clearly states the tool returns the rashi and retrograde status for the 9 grahas, along with paksha, for any instant in a specified year range. It uses a specific verb ('Return') and resource, and is distinct from sibling tools like get_astro_events or find_matching_dates.

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?

Provides clear context with example questions ('which planets are retrograde right now?', 'sky snapshot for 500 CE') indicating appropriate use cases. It does not explicitly exclude alternatives or mention sibling tools, but the examples and focus on planetary positions make the intended usage clear.

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

A4.7/5.0

Disambiguation5/5

Each tool targets a distinct query type: planetary conjunctions, panchang date matching, event lists, nearest events, and position snapshots. Even the similar-looking get_astro_events and get_nearest_event are clearly differentiated by range vs. nearest-neighbor scope.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern: find_copresence, find_matching_dates, get_astro_events, get_nearest_event, get_planetary_positions. 'find_' for search operations and 'get_' for retrieval operations, with snake_case throughout.

Tool Count5/5

Five tools is well within the ideal 3-15 range for a domain-specific server. Each tool covers a meaningful, non-redundant capability for astronomical and panchang time travel, and there is no bloat or triviality.

Completeness4/5

The set covers major workflows: positions, events, conjunctions, and panchang-based date search. The only notable gap is a direct 'panchang for a specific date' lookup, which find_matching_dates cannot handle without constraints and which is explicitly delegated to another MCP server. This is a minor workaround rather than a dead end.

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