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get_aave_reserves

Retrieve all active AAVE lending reserves on a given chain, including supply APY, borrow APY, and TVL. Returns markets sorted by total liquidity.

Instructions

Use this when the user asks about AAVE lending markets, available assets, supply APY, borrow APY, TVL, utilization rate, collateral factors, or liquidation thresholds on a specific chain. Returns all active reserves sorted by total liquidity (TVL). RATE CONVERSION: liquidityRate and variableBorrowRate are in RAY units (1e27). Supply APY % = liquidityRate / 1e27 * 100. Borrow APY % = variableBorrowRate / 1e27 * 100. Amounts are in native token units — divide by 10^decimals for human-readable. Ideal for: 'What assets can I lend on Arbitrum?', 'What is USDC supply rate on Base?', 'Show me all AAVE V3 markets on Polygon'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainYesChain identifier (e.g. ethereum, base, arbitrum, polygon, optimism, avalanche). Use list_aave_chains to see all options.
includeInactiveNoSet true to include frozen, paused, or inactive reserves. Default false (active only).
Behavior4/5

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

No annotations provided, so description carries full burden. Discloses rate units (RAY, 1e27), conversion formulas for APY percentages, and decimal handling for amounts. Does not mention pagination or data freshness, but for a straightforward read tool this is sufficient.

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?

Front-loaded with purpose and usage context. Multiple sentences but each contributes: usage trigger, sorting, rate conversion, amount units, and example queries. Slightly verbose (could trim example list) but still efficient.

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 no output schema and no annotations, the description covers parameter usage, return format interpretation (rates, amounts, sorting), and common queries. Does not detail the JSON structure of each reserve, but the explanations of RAY and decimals make the output understandable.

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?

Schema covers both parameters fully (100% coverage). Description adds valuable context: chain parameter references list_aave_chains for valid options, and includeInactive is explained with default behavior. Also explains return value interpretation (rate conversion, amount decimals) beyond schema.

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?

Describes exactly what the tool does: returns all active AAVE reserves sorted by TVL for a given chain. Clearly distinguishes from siblings like get_aave_reserve (single reserve) and find_best_rates (rate comparison) by specifying the scope and sorting.

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?

Explicitly states when to use (user asks about AAVE markets, supply/borrow rates, etc.) and provides concrete example queries. References sibling tool list_aave_chains for valid chain values. Lacks explicit exclusion guidance (e.g., when to use other tools) but examples cover common cases.

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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