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obol

obol

by halfkey
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

obol_lst_yields

Compare Solana LST yields across jitoSOL, mSOL, bSOL, jupSOL, hSOL using Sanctum APYs and Jupiter exchange rates. Costs $0.02 USDC per request.

Instructions

Compare LST yields across Solana — jitoSOL, mSOL, bSOL, jupSOL, hSOL, and more. APYs from Sanctum, exchange rates from Jupiter. Costs $0.02 USDC.

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": "obol_lst_yields"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.1

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently mentions the $0.02 USDC cost and data sources (Sanctum for APYs, Jupiter for exchange rates), which adds useful context. However, it does not mention whether the operation is read-only, potential errors, or any rate limits, leaving gaps for an agent. The cost and data source details earn it a 3 rather than a 2.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: three short sentences that front-load the primary purpose ('Compare LST yields across Solana') before providing supporting details (examples, data sources, cost). Every sentence adds value with no redundancy. It is an exemplar of efficient, well-structured tool documentation.

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?

Given that the tool has no parameters and no output schema, the description covers the essential aspects: what it does, the specific assets, data sources, and cost. It does not specify the exact format of the returned comparison, but that is inferable from the stated purpose. For a tool of this simplicity, the description is nearly complete, meriting a 4.

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?

The tool has zero parameters, so the schema is trivially covered. Per the calibration rule, a baseline of 4 is given for tools with no parameters. The description does not need to explain parameters and effectively communicates that no inputs are required.

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 clearly states the verb 'Compare' and the resource 'LST yields across Solana,' with specific examples (jitoSOL, mSOL, bSOL, jupSOL, hSOL). This distinguishes it from siblings like obol_token_price (price only) and obol_defi_positions (broader positions), making the tool's unique purpose unmistakable.

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

Usage Guidelines4/5

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

The description implies when to use it (when comparing LST yields on Solana) but does not explicitly mention alternatives or when-not-to-use scenarios. Since the context is clear and the tool's purpose is distinct from its siblings, a score of 4 is appropriate for clear context without exclusions.

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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