AlphaYou: Smart Money Intel

Check smart money activity

get_smart_money

Read-only

Use this for what smart money, Congress or politicians, insiders, funds, influencers or top traders are buying, selling, holding or saying, and where smart money is stacking up. The activity filter accepts buy (buying, adding, accumulating), sell (selling, reducing) or all. Category congress covers politicians, and the actor filter accepts names such as Pelosi or Berkshire. Omitting the ticker returns a bounded discovery preview; a ticker returns security research. Actor and activity filters precede the three-row cap, but underlying coverage remains bounded. Fund changes are reported holdings, influencer posts are commentary, trader positions are derivatives and government awards have no buy/sell direction. Filings and commentary retain original source links. Derivative previews identify Hyperliquid via AlphaYou and source observation times, without trading or copying links. Identical displayed rows are grouped; matchingStoredRows is not a distinct transaction count. This is not a market-wide convergence ranking.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_smart_money"
  }
}

Input Schema

Name	Required	Description	Default
`actor`	No	Only this person or fund, by name
`ticker`	No	US stock ticker, like NVDA
`activity`	No	Only buying, only selling, or both	all
`category`	No	Which smart money source to read	all

Output Schema

Name	Required	Description	Default
`ticker`	Yes
`sources`	Yes
`retrievedAt`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 13, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "retrievedAt": {
+      "type": "string"
+    },
+    "sources": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "category": {
+            "type": "string"
+          },
+          "status": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "category",
+          "status"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "ticker": {
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "ticker",
+    "retrievedAt",
+    "sources"
+  ],
+  "type": "object"
+}

Changed4 schema fields changedNov 12, 2026
- addedInput schema / properties / activity / description
```
Added value: +"Only buying, only selling, or both"
```
- addedInput schema / properties / actor / description
```
Added value: +"Only this person or fund, by name"
```
- addedInput schema / properties / category / description
```
Added value: +"Which smart money source to read"
```
- addedInput schema / properties / ticker / description
```
Added value: +"US stock ticker, like NVDA"
```
First observedOct 11, 2026

TDQS

A4.2/5.0

Behavior5/5

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

Annotations already declare readOnly/openWorld/non-destructive, but the description goes well beyond them: it discloses a three-row cap, that filters precede the cap while underlying coverage stays bounded, that fund changes are lagged reported holdings, influencer content is commentary, trader positions are derivatives, and government awards carry no direction. It also explains row grouping and that matchingStoredRows is not a distinct transaction count, which prevents a very plausible misreading of the output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and the ticker/no-ticker behaviour are front-loaded and every caveat carries information, but the middle is an unstructured wall of loosely concatenated clauses whose relationship to each other is unclear. It would be substantially more scannable as short labelled sentences grouped by output behaviour versus data-source caveats.

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?

With four optional parameters, no required inputs, and an output schema already present, the description need not explain return shape. It instead covers the things the schema cannot: result capping, bounded coverage, per-source interpretation, source attribution and the meaning of row counts. Nothing an agent needs in order to call this correctly is missing.

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%, so the baseline would be 3, but the description adds real semantic depth: activity values are glossed as buying/adding/accumulating vs selling/reducing, category 'congress' is tied to politicians, and actor is illustrated with Pelosi or Berkshire. This makes enum choices concrete rather than abstract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names specific verbs and resources: it reports what smart money, Congress, insiders, funds, influencers and top traders are buying, selling, holding or saying. It also states what it is not ('not a market-wide convergence ranking'), which indirectly points at get_smart_money_overlap. The split between tickerless discovery preview and ticker-based security research further pins down what the tool returns, though it never names the sibling it should be preferred over.

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?

'Use this for...' plus the omission-of-ticker rule gives concrete conditions under which the tool is the right choice, and the negation about convergence ranking rules out a competing use case. What is missing is an explicit routing statement like 'use get_smart_money_overlap instead when...' or any prerequisite/exclusion list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All AlphaYou: Smart Money Intel tools Inspect

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