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buy_yields_protocol_spark-savings

Paid. Live DeFi yields for spark-savings: its pools across chains with APY, TVL, 7d APY change (DefiLlama data). $0.01 USDC on Base or Solana. No account, no API key. Failed calls not charged. URL https://southpow.media/v1/yields/protocol/spark-savings.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "buy_yields_protocol_spark-savings"
  }
}

Input Schema

NameRequiredDescriptionDefault
sortNotvl (default) or apy
limitNoRows, 1-100 (default 20)
min_tvl_usdNoMinimum pool TVL in USD (default 100000)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full burden and does a good job: it declares the tool is paid ($0.01 USDC on Base or Solana), that no account or API key is needed, and that failed calls are not charged — all behavior an agent cannot infer from the schema. It omits refresh cadence and response shape, which keeps it from a 5.

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?

Information is front-loaded: 'Paid.' immediately, then the data scope, then payment/access terms. Sentences are terse and every element (cost, chains, failure policy, endpoint URL) is useful, though the telegraphic phrasing borders on choppy.

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 3-optional-param read tool with no annotations and no output schema, the definition covers what is returned, what it costs, how to pay, and failure charging. The main residual gap is output shape/pagination (e.g., how many rows come back and in what structure), which the agent must discover by calling.

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%, so the three optional parameters (sort, limit, min_tvl_usd) are already documented with defaults in the schema. The description adds nothing about their semantics or interaction, which is acceptable but no better than the baseline.

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 names a specific verb+resource ('Live DeFi yields for spark-savings') and enumerates the returned fields (APY, TVL, 7d APY change, DefiLlama as source), so an agent knows exactly what data it gets. It stops short of a 5 because it never distinguishes itself from adjacent siblings such as buy_yields_protocol_sparklend or buy_yields_chain_*; the reader must infer the protocol scoping from the tool name.

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 is only implied by the scope phrase — an agent can infer this is the tool for spark-savings pool yields. There is no explicit 'use this when…' statement, no exclusions, and no routing to alternatives like the chain-level or SparkLend yield tools when the user actually wants those.

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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