get_fear_greedCrypto Fear & Greed index (0-100) with classification. Free.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | the get_fear_greed payload | |
| tool | Yes | the tool that produced this payload |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "data": {
+ "additionalProperties": {},
+ "description": "the get_fear_greed payload",
+ "propertyNames": {
+ "type": "string"
+ },
+ "type": "object"
+ },
+ "tool": {
+ "const": "get_fear_greed",
+ "description": "the tool that produced this payload",
+ "type": "string"
+ }
+ },
+ "required": [
+ "tool",
+ "data"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds minimal extra behavioral context: it is free and includes a classification. It does not contradict annotations, but it does not disclose rate limits, update frequency, or other operational nuances.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded: it states the data source, scale, output characteristic, and cost in two short sentences. Every word adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 and comprehensive annotations, the description is sufficient for an agent to understand what the tool provides and to invoke it correctly. Missing usage guidance is captured under usage_guidelines, not completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters)Skip, and schema coverage is 100% with an empty properties object. There are no parameters requiring additional semantic explanation, so the baseline of 4 applies; the description need not add parameter detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies the specific resource (Crypto Fear & Greed index) and adds the scale (0-100) and classification aspect, making the purpose clear. It lacks an explicit verb like 'returns' or 'retrieves', and it does not explicitly differentiate itself from sibling tools, though the resource is unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. The word 'Free' hints at a cost advantage but does not state a use case, prerequisites, or exclusions. An agent would not know when this is preferred over other data tools.
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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