SiteCheck Crypto & Finance

ETF.com profile for a US-listed ETF: name, issuer, one-line

finance_etf_com

Read-only

ETF.com profile for a US-listed ETF: name, issuer, one-line strategy description, inception date, expense ratio, assets under management, benchmark, index tracked, category and fee note. From etf.com's public fund pages (their structured data) via a residential proxy. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbol": "<symbol>"
    },
    "name": "finance_etf_com"
  }
}

Input Schema

Name	Required	Description	Default
`symbol`	Yes	ETF ticker, e.g. SPY, QQQ, VTI

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A3.9/5.0

Behavior5/5

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

Annotations only say readOnly and openWorld; the description goes well beyond by disclosing the data source (etf.com public fund pages, structured data, residential proxy), the billing model ($0.002 USDC per successful call via x402 on Base/Solana/Arc), and the failure policy (no charge on failure). Payment precondition is exactly the kind of operational trait an agent cannot get from annotations or schema.

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?

Field inventory is front-loaded in one sentence, then source and pricing in a second; no filler. It is dense but every clause carries information an agent needs before calling a paid proxy-backed endpoint.

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?

With an output schema present and a single well-documented parameter, the description need only cover sourcing, coverage limits and cost, and it does. The only omission is any note on error behavior or rate limits beyond the no-charge-on-failure rule.

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?

Schema description coverage is 100% for the single 'symbol' parameter, including examples (SPY, QQQ, VTI), so the schema does the work. The description's field list describes the return payload rather than adding meaning to the input, which lands at the baseline for a fully documented one-parameter 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?

States a specific resource (ETF.com profile for a US-listed ETF) and enumerates exactly what fields come back: issuer, expense ratio, AUM, benchmark, index tracked, category. An agent can tell it returns static fund metadata, not prices. It stops short of naming which sibling it replaces, so differentiation from finance_yahoo_finance or dev_morningstar is left to inference.

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 scope 'US-listed ETF' implicitly tells the agent when it applies, and the cost line implies a paid-data lookup rather than a bulk scan. But there is no explicit when-to-use/when-not guidance and no pointer to an alternative for non-US ETFs, ETF pricing, or holdings data.

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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