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buy_yields_protocol_liquity-v2

Paid. Live DeFi yields for liquity-v2: 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/liquity-v2.

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_liquity-v2"
  }
}

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

B3.4/5.0
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 solid job: it discloses the paid model ($0.01 USDC on Base or Solana), the absence of auth requirements (no account, no API key), and that failed calls are not charged. That failure/payment semantics is exactly the sort of behavior an agent needs before committing. It stops short of describing response shape or pagination behavior.

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 tight and front-loaded, leading with the paid flag and the core payload before pricing and URL. Every sentence carries information, though the raw endpoint URL is somewhat redundant given the tool's own invocation path.

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 zero-required-param read tool with no output schema and no annotations, the description covers cost, auth, and the headline metrics well. It leaves gaps around what the returned row structure looks like and how limits/pagination behave, which matters since no output schema exists to fill that in.

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%, so the three optional params (sort, limit, min_tvl_usd) are already fully documented in the schema. The description's mention of APY/TVL/7d change loosely corroborates the sort options but adds no syntax, defaults, or format detail beyond what the schema already states. Baseline 3 is appropriate.

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 gives a specific verb and resource: live DeFi yields for the liquity-v2 protocol, listing the metric fields (APY, TVL, 7d APY change) and the data source (DefiLlama). The protocol-specific name separates it cleanly from the other buy_yields_protocol_* siblings, though it never explicitly distinguishes itself from the near-identical buy_yields_protocol_liquity-v1 sibling.

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

Usage Guidelines2/5

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

There is no when-to-use guidance at all. The description never says when an agent should prefer this protocol endpoint over buy_yields_chain_*, buy_yields_token_*, or the v1 variant, and it offers no exclusions or prerequisites beyond payment mechanics.

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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