whale-insights

golden_alerts_monthly

Read-onlyIdempotent

Golden Alerts permanent monthly archive — Returns the permanent monthly archive of Golden Alert activity — one row per calendar month, aggregated from daily snapshots before they are purged. This archive is never deleted and grows indefinitely, providing AI agents with long-term trend data on alert severity and top tokens across months and years. Each month includes: totalCount (total alerts that month), highCount/mediumCount/lowCount (severity breakdown), topTokens (5 most-active tokens), daysInMonth (days with data), avgPerDay (daily average). Months with fewer than 20 daily records are excluded to ensure statistical accuracy. Data source: CryptoWhaleInsights own signal_history database (49,000+ on-chain signals). No authentication required. 60 req/min. 5-min cache. — Use this for long-term monthly archive data; use the corresponding live or daily-history tool for current or finer-grained data.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`total`	No
`months`	No
`updatedAt`	No
`dataSource`	No
`attribution`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 3, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "attribution": {
+      "$ref": "#/components/schemas/Attribution"
+    },
+    "dataSource": {
+      "type": "string"
+    },
+    "months": {
+      "items": {
+        "properties": {
+          "avgPerDay": {
+            "type": "number"
+          },
+          "daysInMonth": {
+            "type": "integer"
+          },
+          "highCount": {
+            "type": "integer"
+          },
+          "lowCount": {
+            "type": "integer"
+          },
+          "mediumCount": {
+            "type": "integer"
+          },
+          "month": {
+            "description": "First day of the month (YYYY-MM-01, UTC).",
+            "format": "date",
+            "type": "string"
+          },
+          "topTokens": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "totalCount": {
+            "type": "integer"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "total": {
+      "type": "number"
+    },
+    "updatedAt": {
+      "format": "date-time",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

AddedJun 26, 2026

TDQS

A5/5.0

Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive, and the description adds substantial behavior beyond that: the archive never gets deleted, data is aggregated from daily snapshots before purging, no auth required, 60 req/min rate limit, 5-min cache, and a statistical-minimum exclusion threshold. No contradiction exists.

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 long but every sentence carries distinct information: purpose, aggregation behavior, field list, exclusion rule, data source, auth/rate/cache constraints, and sibling routing. The most important identity information is front-loaded before contextual details.

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 is complete: it covers what the resource is, how it is computed, what fields it returns, when not to use it, rate limits, caching, authentication, and data provenance. Nothing an agent needs to select or invoke the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the baseline is 4. The description goes beyond this by enumerating every output field (totalCount, severity counts, topTokens, daysInMonth, avgPerDay), explaining the monthly aggregation semantics, and stating the minimum-record threshold. This fully compensates for the empty input schema.

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?

Description starts with a specific verb and resource: 'Returns the permanent monthly archive of Golden Alert activity.' It explicitly distinguishes itself from live/daily-history tools and clarifies the monthly aggregation granularity, making it unmistakable among siblings like golden_alerts_history and golden_alerts_snapshot.

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?

Explicitly states when to use this tool: 'Use this for long-term monthly archive data; use the corresponding live or daily-history tool for current or finer-grained data.' It also documents the 20-record exclusion rule, which is a concrete selection criterion for using the data.

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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