Noaa Spc

Storm Reports

storm_reports

Read-onlyIdempotent

Fetch NOAA SPC preliminary storm reports CSV for a given date (YYMMDD, default today UTC) filtered by kind: tornado, wind, hail, or filtered (combined). Returns raw CSV with time, location, magnitude, and remarks.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`date`	No	YYMMDD (default today UTC)
`kind`	No	tornado \| wind \| hail \| filtered (default)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`body`	Yes	CSV data of preliminary storm reports
`format`	Yes	Response format

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedMay 22, 2026

addedInput schema / examples

Added value: +[
+  {
+    "date": "250115",
+    "kind": "tornado"
+  },
+  {
+    "kind": "hail"
+  }
+]

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "body": {
+      "description": "CSV data of preliminary storm reports",
+      "type": "string"
+    },
+    "format": {
+      "description": "Response format",
+      "enum": [
+        "csv"
+      ],
+      "type": "string"
+    }
+  },
+  "required": [
+    "format",
+    "body"
+  ],
+  "type": "object"
+}

First observedMay 18, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, and non-destructive nature. The description adds context: returns raw CSV with specific fields (time, location, magnitude, remarks), which is consistent with annotations. No contradictory behavior mentioned.

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 a single, well-structured sentence that front-loads the action and includes all essential details (resource, date format, filter options, output format). No extraneous words.

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 tool has only two optional parameters, an output schema, and comprehensive annotations, the description covers the return format and parameter defaults. It is fully sufficient for an agent to understand and invoke the tool.

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?

Schema coverage is 100% with descriptions for both parameters. The description adds meaning beyond the schema by explaining the date format (YYMMDD, default today UTC) and the meaning of each kind value (tornado, wind, hail, filtered/combined). This helps an agent understand valid inputs.

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 'Fetch NOAA SPC preliminary storm reports CSV for a given date... filtered by kind', specifying both the verb (fetch) and resource (storm reports). It distinguishes from siblings like convective_outlook by focusing on preliminary reports in CSV format.

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?

The description implies usage for fetching storm reports by date and kind, but does not explicitly state when to use this tool versus alternatives (e.g., convective_outlook). No exclusion criteria or when-not guidance is provided.

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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