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NaniDAO

agentek-eth

by NaniDAO

getYieldTool

Analyze and compare DeFi yield opportunities across protocols using DefiLlama data. Filter by chain, project, token, risk level, and APY thresholds to identify optimal returns.

Instructions

Analyzes and compares yield opportunities from DefiLlama across all DeFi protocols

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoOptional filter for specific chain (e.g., Ethereum, Arbitrum)
projectNoOptional filter for specific project (e.g., Aave, Lido)
symbolNoOptional filter for specific token symbol (e.g., ETH, USDC)
stablecoinNoOptional filter for stablecoin yields only
minApyNoOptional minimum APY threshold (e.g., 5 for 5%)
maxRiskNoOptional maximum risk level (low, medium, high)
protocolNoOptional filter for specific protocol (e.g., Aave, Compound)
assetNoOptional filter for specific asset (e.g., ETH, USDC)
chainIdNoOptional chain ID filter (e.g., 1 for Ethereum, 10 for Optimism)
limitNoMaximum number of results to return
Behavior2/5

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 mentions analysis and comparison but lacks details on output format, data freshness, rate limits, authentication needs, or potential side effects. For a tool with 10 parameters and no output schema, this is a significant gap in transparency.

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 a single, efficient sentence that directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, with every word contributing to understanding the purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (10 parameters, no output schema, no annotations), the description is insufficient. It lacks details on what the analysis returns, how results are structured, or any behavioral traits like error handling or data sources. For a tool that analyzes and compares yields, this leaves critical gaps for an AI agent.

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?

The schema description coverage is 100%, with each parameter well-documented in the schema itself. The description adds no additional parameter semantics beyond implying filtering across protocols, which is already covered by the schema. This meets the baseline score of 3 when schema coverage is high.

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 clearly states the action ('analyzes and compares') and resource ('yield opportunities from DefiLlama across all DeFi protocols'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'compareYieldTool' or 'getYieldHistoryTool', which appear related to yield analysis but with different scopes or methodologies.

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?

No guidance is provided on when to use this tool versus alternatives such as 'compareYieldTool' or 'getYieldHistoryTool'. The description implies a broad analysis across all protocols but doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage from context alone.

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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