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whale-insights

by com.cryptowhaleinsights
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social_summary

Read-onlyIdempotent

Get aggregate market mood — overall sentiment score/label + top 5 tokens (no auth; use sentiment_history for per-token time-series) — Non-gated social sentiment summary: the aggregate market-mood score/label plus the top 5 tokens by sentiment (AI insight text excluded). Served from cache (no per-request AI cost). Full per-token AI insights require a Max Alpha subscription. Cached ~5min.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalNo
marketNo
tokensNo
updatedAtNo
attributionNo
requiredTierForFullNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "attribution": {
+      "$ref": "#/components/schemas/Attribution"
+    },
+    "market": {
+      "properties": {
+        "bearishCount": {
+          "type": "number"
+        },
+        "bullishCount": {
+          "type": "number"
+        },
+        "label": {
+          "type": "string"
+        },
+        "neutralCount": {
+          "type": "number"
+        },
+        "score": {
+          "type": "number"
+        },
+        "topMentioned": {
+          "items": {
+            "type": "string"
+          },
+          "type": "array"
+        },
+        "updatedAt": {
+          "format": "date-time",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "requiredTierForFull": {
+      "type": "string"
+    },
+    "tokens": {
+      "items": {
+        "properties": {
+          "name": {
+            "type": "string"
+          },
+          "overallScore": {
+            "type": "number"
+          },
+          "priceChange24h": {
+            "type": "number"
+          },
+          "sentiment": {
+            "type": "string"
+          },
+          "symbol": {
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "total": {
+      "type": "number"
+    },
+    "updatedAt": {
+      "format": "date-time",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already provide readOnly/openWorld/idempotent/destructive hints, and the description adds meaningful behavior beyond that: data is served from cache, cached ~5 minutes, no per-request AI cost, AI insight text is excluded, and stronger insights are gated behind a Max Alpha subscription.

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?

The description is front-loaded with the core purpose and useful routing, but it is redundant: the aggregate score/label plus top 5 tokens is stated twice, and caching is mentioned twice ('Served from cache' and 'Cached ~5min'). It could be tightened without losing information.

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?

For a zero-parameter, read-only tool with an output schema, the description covers everything needed to invoke it correctly: what it returns, auth requirements, caching behavior, subscription limitations, and the relevant sibling alternative.

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 tool has zero parameters and schema coverage is 100%, so the description has no parameter semantics to add. The baseline for zero-parameter tools is 4; the description stays there by focusing on output and access behavior instead.

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 opens with a specific verb and resource ('Get aggregate market mood') and defines the exact output: overall sentiment score/label plus top 5 tokens. It also distinguishes itself from the sibling sentiment_history by explicitly naming it, so an agent can tell which tool to use.

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

Usage Guidelines5/5

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

It explicitly says 'use sentiment_history for per-token time-series', providing a clear alternative and the condition that selects the other tool. It also states 'no auth', 'non-gated', and that full AI insights require a subscription, giving clear when-to-use context.

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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