Polygon Io

Splits

splits

Read-onlyIdempotent

Historical stock splits for a US-listed ticker, from Massive (formerly Polygon.io): split ratio, execution date, ticker. Use to adjust historical price comparisons across split events.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`ticker`	No
`execution_date`	No

Output Schema

TableJSON Schema

Name	Required	Description
`count`	No	Number of results
`status`	No	API response status
`results`	No	Stock splits data
`next_url`	No	Next page URL if available

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedMay 27, 2026

addedInput schema / examples

Added value: +[
+  {
+    "limit": 10,
+    "ticker": "AAPL"
+  }
+]

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of results",
+      "type": "number"
+    },
+    "next_url": {
+      "description": "Next page URL if available",
+      "type": "string"
+    },
+    "results": {
+      "description": "Stock splits data",
+      "items": {
+        "properties": {
+          "execution_date": {
+            "description": "Execution date",
+            "type": "string"
+          },
+          "split_from": {
+            "description": "Split from ratio",
+            "type": "number"
+          },
+          "split_to": {
+            "description": "Split to ratio",
+            "type": "number"
+          },
+          "ticker": {
+            "description": "Ticker symbol",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "status": {
+      "description": "API response status",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

First observedMay 20, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds context about the data source and the purpose (adjusting historical price comparisons), but does not disclose details like pagination, rate limits, or data coverage limitations beyond 'US-listed ticker'.

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 two sentences, front-loaded with the core purpose and data source, and ends with a clear use case. Every word earns its place; no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (3 optional parameters, no required fields) and the presence of an output schema, the description is fairly complete. It explains the data source, the fields, and the use case. However, it could mention that all parameters are optional (since none are required) and clarify the 'limit' parameter's role, but the output schema likely covers return structure.

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?

Schema description coverage is 0%, so the description must compensate. It mentions 'split ratio, execution date, ticker' as fields, which maps to the 'ticker' and 'execution_date' parameters, but does not explain the 'limit' parameter or provide format details (e.g., date format). The description adds some meaning but leaves gaps for the 'limit' parameter and date format.

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 provides historical stock splits for a US-listed ticker, specifying the data source (Massive, formerly Polygon.io) and the key fields (split ratio, execution date, ticker). It distinguishes itself from siblings like 'dividends' and 'aggregates' by focusing on split events.

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 explicitly states the use case: 'Use to adjust historical price comparisons across split events.' It implies when to use this tool (when needing split data) but does not explicitly mention when not to use it or alternatives, though the sibling list includes related tools like 'dividends' and 'aggregates'.

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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