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Hryhorii77

aero-allocator

by Hryhorii77

scan_pools

Retrieve live TVL, staked TVL, fee tier, and emissions for Aerodrome gauge-enabled pools on Base, sorted by staked TVL. Use for market overview before demand prediction.

Instructions

Scan Aerodrome (Base) gauge-enabled pools with live TVL, staked TVL, fee tier and emissions. Sorted by staked TVL. Use this for a market overview before predicting demand.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax pools to return
minTvlUsdNoMinimum pool TVL in USD
Behavior3/5

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

No annotations are provided, so the description must convey behavior. It describes the tool as scanning for live data and sorting by staked TVL. It does not explicitly state read-only nature or any side effects, but the verb 'scan' implies a read operation. The description adds value over no description but lacks explicit behavioral guarantees.

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 two sentences long with no wasted words. It front-loads the core action and output fields, then provides usage guidance. Every sentence adds value.

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 the tool has no output schema, the description lists the main return fields (live TVL, staked TVL, fee tier, emissions) and states the sort order. It also mentions the platform (Aerodrome on Base) and ties to sibling tools implicitly. A minor gap is not describing each field in detail, but for a scan tool this is sufficient.

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%, meaning the input schema already documents parameters (limit, minTvlUsd) with descriptions and defaults. The tool description does not add additional meaning to these parameters beyond what is in the schema, so baseline score of 3 is appropriate.

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 action ('Scan'), the resource ('Aerodrome (Base) gauge-enabled pools'), and the returned fields (live TVL, staked TVL, fee tier, emissions). It distinguishes itself from siblings by positioning as a market overview tool before predicting demand.

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 gives explicit usage context: 'Use this for a market overview before predicting demand.' This implies it is a preliminary step to predictive tools like predict_demand. It does not specify when not to use it, but the context is clear enough.

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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