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Crypto ETF Issuer Fee Revenue

get_issuer_revenue
Read-only

Get estimated sponsor fee revenue of US spot crypto ETFs: net assets times the prospectus sponsor fee, with temporary fee waivers applied. Per fund: net assets, nominal and effective fee (percent per year), revenue per day and annualised at current assets, and the sum for the last 30 days where a daily series exists. Totals by issuer and for the whole market. Arithmetic on the published fee, not the issuer's reported revenue; the sponsor's share of staking rewards is not included.

Input Schema

NameRequiredDescriptionDefault
assetNoOptional asset filter for the fund list: btc, eth, sol, xrp, hyp, doge, link, avax, hbar, ltc, bnb, dot, sui, near, trx, zec

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already establish that this is a safe read-only operation, and the description adds valuable methodological transparency beyond that: it is an estimate based on published fees, applies temporary waivers, and excludes staking rewards. It does not discuss freshness, update cadence, or limits, so it is strong but not exhaustive.

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 front-loaded with the tool's purpose and then efficiently covers output shape and caveats. It is dense, especially the long enumeration of per-fund fields, but every sentence contributes useful information.

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 no output schema, the description carries the burden of explaining what is returned, and it does so by naming the per-fund and aggregate fields and the estimation caveats. Combined with the fully documented asset parameter, it is complete enough to invoke correctly, though it could say more about time coverage and data freshness.

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 coverage is 100% and the single optional asset parameter is fully documented in the schema. The description does not add any parameter-specific semantics; it only describes the computed output, so the baseline of 3 is appropriate.

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 states a specific verb and resource: estimated sponsor fee revenue of US spot crypto ETFs. It is clearly distinct from sibling tools like get_etf_holdings and get_fund_flows, and the calculation basis (net assets times prospectus sponsor fee) further sharpens the purpose.

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 when the tool is useful by specifying the exact metric computed, but it does not explicitly say when to use it versus alternatives or when not to use it. No sibling tools are named or ruled out, leaving routing to the agent's inference.

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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