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Echo Sentiment — XLM Market Sentiment

$0.10 — get_prediction_market_pulse

get_prediction_market_pulse

PAID $0.02 per call (https://api.6766587364.lol/v1/prediction). Polymarket pulse: top prediction markets by 24h volume with implied odds — event probability signal for forecasting agents. 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
limitNo
api_keyNo
paymentNo
bundle_tokenNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

The description discloses the paid nature, the endpoint, and the payment-until-authenticated behavior, which is especially valuable since no annotations exist. However, the title says $0.10 while the description says $0.02 per call, creating cost ambiguity, and it omits rate limits, error behavior, and post-payment response details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences with cost and endpoint information front-loaded, followed by purpose and authentication mechanics. It is concise and mostly free of fluff, though the price mismatch and slightly compressed payment explanation prevent a top score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a paid tool with no annotations, no output schema, and four parameters, the description should explain the response format, limit semantics, and payment edge cases. It covers the payment requirement well but leaves these gaps, so an agent may not fully understand the resulting data or how to control it.

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

Parameters3/5

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

With 0% schema coverage, the description compensates by explaining api_key, payment, and bundle_token, including how they relate to headers and free-tier usage. However, the limit parameter is completely unexplained, leaving its default, format, and meaning unclear.

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 clearly identifies the resource (Polymarket pulse), the data returned (top prediction markets by 24h volume with implied odds), and the intended use (event probability signal for forecasting agents). This distinguishes it from sibling sentiment and market-breadth tools even without an explicit verb.

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

Usage Guidelines3/5

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

The description implies a forecasting use case and points to get_free_api_key for credentials, but it never explicitly states when to prefer this tool over alternatives like get_fear_greed_index or get_market_breadth. No exclusions or alternative-selection conditions are provided.

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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