whale-insights

fear_greed_monthly

Read-onlyIdempotent

Fear & Greed permanent monthly archive — Returns the permanent monthly archive of the Fear & Greed index — one row per calendar month, aggregated from daily snapshots before they are purged. Never deleted; grows indefinitely providing AI agents with macro sentiment context across months and years. Each month includes: avgScore (0–100 average), minScore, maxScore, dominantClassification (Extreme Fear / Fear / Neutral / Greed / Extreme Greed), fearDays (days with score<40), greedDays (score>60), neutralDays, daysInMonth. Months with fewer than 20 daily records are excluded. 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": {
+          "avgScore": {
+            "type": "number"
+          },
+          "daysInMonth": {
+            "type": "integer"
+          },
+          "dominantClassification": {
+            "type": "string"
+          },
+          "fearDays": {
+            "type": "integer"
+          },
+          "greedDays": {
+            "type": "integer"
+          },
+          "maxScore": {
+            "type": "integer"
+          },
+          "minScore": {
+            "type": "integer"
+          },
+          "month": {
+            "format": "date",
+            "type": "string"
+          },
+          "neutralDays": {
+            "type": "integer"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "total": {
+      "type": "number"
+    },
+    "updatedAt": {
+      "format": "date-time",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

AddedJun 26, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds meaningful behavioral details: 'Never deleted; grows indefinitely', 'Months with fewer than 20 daily records are excluded', 'No authentication required. 60 req/min. 5-min cache.' No contradiction with annotations.

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 front-loaded with the definition, then covers row structure, exclusions, access limits, and use-case routing without fluff. Each sentence adds distinct value.

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 output schema and safe annotations, the description is complete: it explains aggregation source, purge timing, exclusions, rate limits, caching, and the appropriate sibling choice.

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?

There are zero parameters, so the baseline of 4 applies. The description adds no parameter constraints (there are none), but it does explain the returned row composition (avgScore, minScore, etc.) which is helpful context even though it isn't parameter semantics.

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?

Clearly identifies a specific verb ('returns') and resource ('permanent monthly archive of the Fear & Greed index'), with specifics like 'one row per calendar month, aggregated from daily snapshots'. It also distinguishes itself from live/daily-history counterparts, so an agent can differentiate it from siblings like fear_greed or fear_greed_history.

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 'Use this for long-term monthly archive data; use the corresponding live or daily-history tool for current or finer-grained data.' This provides both a positive use case and an alternative direction.

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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