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Vedaksha

by arthiqlabs
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Rust
Hybrid

compute_composite

Read-only

Calculate the composite midpoint chart of two Vedic charts: for each graha, find the shorter-arc longitude midpoint and mean speed, pairing same-name grahas.

Instructions

Compute the midpoint composite chart of two charts: for each graha, the shorter-arc midpoint of its longitude in the two charts, and the arithmetic mean of its two speeds. The two charts must carry the SAME graha names — each graha is paired with its namesake, not with whatever happens to sit at the same position in a list — and a name present in one chart but not the other is an error naming that graha. Longitudes only: this tool needs no birth time, place or ephemeris.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chart_aYesMap of graha name to position for the first chart, e.g. {"Sun": {"longitude": 350.0, "speed": 1.0}}. `speed` is optional and defaults to 0.
chart_bYesMap of graha name to position for the second chart. Must have exactly the same graha names as chart_a.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
planetsYesOne entry per graha present in both charts.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv8.0.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "planets": {
+      "description": "One entry per graha present in both charts.",
+      "items": {
+        "properties": {
+          "longitude": {
+            "description": "Midpoint longitude in degrees [0, 360).",
+            "type": "number"
+          },
+          "planet": {
+            "description": "Graha name.",
+            "type": "string"
+          },
+          "speed": {
+            "description": "Mean of the two supplied speeds, in degrees per day.",
+            "type": "number"
+          }
+        },
+        "required": [
+          "planet",
+          "longitude",
+          "speed"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "planets"
+  ],
+  "type": "object"
+}
  2. First observedv7.0.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses important behavioral details: grahas are paired by namesake rather than list position, a name present in one chart but not the other produces an error naming that graha, and the tool ignores everything except longitudes and speeds. This gives an agent accurate expectations about failure modes and matching semantics.

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 three sentences, front-loads the core computation, and each sentence adds essential information: what is computed, matching/error semantics, and data requirements. There is no filler or repetition of schema content.

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 the output schema, input schema, and annotations, the description covers the remaining essentials: prerequisite chart-name identity, error behavior, and what inputs are ignored. An agent can correctly select and invoke the tool with the information provided.

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

Parameters4/5

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

The input schema already documents chart_a, chart_b, longitude, and speed with 100% coverage, so the baseline is 3. The description adds meaningful semantics beyond the schema by clarifying that chart_a and chart_b must contain exactly the same graha names and that matching is by name, not position. This raises it above baseline.

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 names a specific operation, 'compute the midpoint composite chart of two charts,' and defines exactly what is computed: shorter-arc longitude midpoints and arithmetic mean speeds. This clearly distinguishes it from sibling computational tools like compute_synastry or compute_transit.

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?

The description gives clear context on when the tool applies: it works on two charts with matching graha names and needs only longitudes, not birth time/place/ephemeris. It does not explicitly name alternative tools or state when not to use it, so it stops just short of full routing guidance.

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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