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minia2a-mcp

x402-dex-depth

DEX Liquidity Depth: Slippage estimate for large orders across DEX pools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoSize to process
tokenNoToken to process
amountNoAmount to process
addressNoAddress to process
amountUsdNoAmountUsd to process

TDQS

B3.4/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It explains the core function but does not disclose return format, required inputs, data sources, or whether the estimate is live or approximate. This is thin for a tool that an agent must invoke correctly.

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 front-loaded sentence with no filler. It communicates the core purpose immediately and does not waste tokens.

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?

For a tool with 5 optional string parameters, no output schema, no annotations, and a large field of DEX-related siblings, this one-sentence description is not enough. An agent would struggle to know which parameters to provide, what the response looks like, or how this tool differs operationally from other DEX tools.

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%, which gives the baseline of 3 even though the tool description does not add parameter-level meaning. However, the schema descriptions are generic ('Size to process', 'Amount to process', 'Address to process') and do not clarify the relationships or required combinations of size, amount, amountUsd, and address.

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 identifies the tool as a DEX liquidity depth tool that estimates slippage for large orders across DEX pools. This distinguishes it from sibling tools like x402-dex-price and x402-dex-arb, which serve different purposes.

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

Usage Guidelines3/5

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

The phrase 'for large orders' gives some implicit guidance about when the tool is relevant, but the description does not explicitly mention alternatives or state when not to use it. With many DEX-related sibling tools, this is a noticeable gap.

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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TDQS

D1.6/5.0
Disambiguation1/5

The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.

Naming Consistency2/5

Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.

Tool Count1/5

1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.

Completeness2/5

The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.

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