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by io.github.pipeworx-io
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Monthly Radiation

monthly_radiation
Read-onlyIdempotent

Long-term monthly average global / diffuse / direct irradiation on horizontal / inclined plane.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
angleNoSpecific tilt angle (default optimum)
optradNoInclude optimum-angle irradiation (default true)
endyearNoLatest year
horirradNoInclude horizontal irradiation (default true)
latitudeYes
longitudeYes
startyearNoEarliest year, defaults to climate database start

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNoInput parameters echoed back
outputsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "horirrad": true,
+    "latitude": 40.7128,
+    "longitude": -74.006,
+    "optrad": true
+  },
+  {
+    "angle": 25,
+    "endyear": 2020,
+    "latitude": 48.8566,
+    "longitude": 2.3522,
+    "startyear": 2010
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "inputs": {
+      "description": "Input parameters echoed back",
+      "type": "object"
+    },
+    "outputs": {
+      "properties": {
+        "months": {
+          "items": {
+            "properties": {
+              "Bn": {
+                "description": "Direct normal irradiation (kWh/m²)",
+                "type": "number"
+              },
+              "Dh": {
+                "description": "Diffuse irradiation (kWh/m²)",
+                "type": "number"
+              },
+              "H_opt": {
+                "description": "Optimum-angle irradiation (kWh/m²)",
+                "type": "number"
+              },
+              "Hh": {
+                "description": "Horizontal irradiation (kWh/m²)",
+                "type": "number"
+              },
+              "month": {
+                "description": "Month number (1-12)",
+                "type": "integer"
+              }
+            },
+            "type": "object"
+          },
+          "type": "array"
+        }
+      },
+      "type": "object"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds context by specifying the data is 'long-term monthly average,' implying historical data without real-time updates. No contradictions.

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?

One sentence of 12 words, front-loaded with key output. Every word is meaningful; no redundancy.

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?

Adequate given the output schema exists and annotations are rich. However, the description could mention data source or date range defaults. For a 7-parameter tool, slightly more context would help.

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?

With 71% schema description coverage, the schema already documents most parameters. The description adds no new parameter details beyond the resource type. Baseline of 3 is appropriate.

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 'long-term monthly average global / diffuse / direct irradiation on horizontal / inclined plane,' specifying the resource type and orientation, distinguishing it from siblings like `tmy` (weather data) and `pv_performance` (system output).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives (e.g., `tmy` or `pv_performance`). The description lacks context about appropriate use cases or exclusions.

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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