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Echo Sentiment — XLM Market Sentiment

$0.10 — get_arbitrage_opportunities

get_arbitrage_opportunities

PAID $0.10 per call (https://api.6766587364.lol/v1/arb-opportunities). Live CEX<->SDEX arbitrage scanner: net spread %% after fees across venues, with a go/no-go verdict. 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

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the $0.10 per-call cost, the payment-requirement behavior until authenticated, and the live nature of the data. It does not cover rate limits or failure modes, but the key behavioral trait—paid access—is clearly exposed.

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?

Three dense sentences cover price, endpoint, function, output nature, and auth methods without padding. Every sentence contributes information. The title redundantly repeats the price, but the description itself is efficiently front-loaded with the cost.

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

Completeness4/5

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

For a tool with three simple parameters and no output schema, the description provides enough for an agent to invoke it correctly: what it does, what it costs, and how to authorize. It could add expected response shape or failure semantics, but nothing essential is missing for a first call.

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%, so the description must compensate, and it does: each of the three parameters (payment, bundle_token, api_key) is explained as an alternative authentication/payment method. It also directs users to get_free_api_key for obtaining a free-tier key. The only weakness is ambiguity about whether `payment` is a header or a schema parameter.

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 identifies a specific resource ('Live CEX<->SDEX arbitrage scanner') and a clear function: computing net spread after fees and producing a go/no-go verdict. This distinguishes it from sibling market-data tools like get_fear_greed_index or get_market_breadth, though it stops short of naming exactly which sibling it competes with.

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?

Usage context is implied: use this when you need live arbitrage opportunities. The description gives meaningful guidance on how to pay/authenticate, including a pointer to the sibling get_free_api_key, but it never explicitly states when to prefer this tool over alternatives or when not to use it.

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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