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Echo Sentiment — XLM Market Sentiment

$0.01 — get_fear_greed_index

get_fear_greed_index

PAID $0.01 per call (https://api.6766587364.lol/v1/fng). Cheapest tick: Crypto Fear & Greed index (0-100) with its label and a mapped -1..1 sentiment score. One number, no fluff — ideal for a poll loop. Returns a payment requirement until called with a payment header, a prepaid bundle_token, or a free-tier api_key (mint one with get_free_api_key).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
paymentNo
bundle_tokenNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description thoughtfully discloses the cost and identifies the auth precondition: calls return a payment requirement until one of `payment`, `bundle_token`, or free-tier `api_key` is supplied. This is meaningful behavior beyond the schema. It does not detail failure modes beyond the payment gate, but the tool's read-only nature limits severity.

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?

Four short sentences front-load cost and endpoint, then cover result shape, use case, and auth requirements. There is no redundant filler; every clause contributes.

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 one-value market tick with no annotations and no output schema, the description is remarkably complete: it specifies cost, endpoint, result fields, use-case fit, and the full set of authentication paths. An agent can determine how to invoke it and what to expect.

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 0%, yet the description adds semantics for all three parameters: `payment` is a paid header, `bundle_token` is prepaid, and `api_key` can be minted via get_free_api_key. It stops short of specifying exact value formats or how the parameters map to MCP arguments, so it does not fully compensate, but it is much more than the bare schema.

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 explicitly identifies the resource (Crypto Fear & Greed index), the returned payload (0-100 value plus label and -1..1 sentiment score), and frames it as a cheap one-number tick. It is clear about the core function, though it relies on the tool name for the verb and does not name sibling tools to distinguish them.

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?

"Ideal for a poll loop" gives a concrete use case, and the payment/auth guidance states how to call it successfully. It does not explicitly list exclusions or sibling alternatives, but in context the target scenario is clear.

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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