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find_arbitrage

Find cross-venue DEX arbitrage opportunities ranked by gross USD at optimal trade size instead of raw spread, exposing only viable trades. Returns an empty list when no opportunity exists.

Instructions

Scan a chain for cross-venue arbitrage right now: pairs whose price differs enough between DEXes to be worth trading, ranked by GROSS USD AT THE OPTIMAL TRADE SIZE — not by raw spread, because a wide spread on a tiny pool is not an opportunity. Returns an empty list when there is nothing, which is a real answer. Excludes gas, MEV and execution risk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoChain to query. Defaults to bsc.
minSpreadBpsNoMinimum cross-venue spread in basis points. Default 20.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It transparently discloses that results are ranked by gross USD at optimal trade size, not raw spread, that an empty list is a valid result, and that gas, MEV, and execution risk are excluded. This provides clear behavioral expectations.

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?

The description is compact and each sentence adds value: it defines the scope, the ranking method, the empty-list behavior, and the exclusions. It is slightly verbose but not redundant.

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?

There is no output schema, but the description indicates the output is a ranked list of opportunities and explicitly states the empty-list case. It also clarifies what is excluded, giving enough context for an agent to interpret results. Minor gaps remain about the exact output format or fields.

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 provides 100% coverage for parameters, each with a description (chain, minSpreadBps). The tool description adds context about ranking by gross USD, but does not add significant new meaning to the parameters beyond what is already in the schema. Baseline 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 tool scans a chain for cross-venue arbitrage opportunities, using the specific verb 'scan' and resource 'chain'. It differentiates from siblings like get_dex_spread and get_best_venue by focusing on a cross-venue, chain-wide scan rather than a specific pair.

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 description mentions 'right now' indicating real-time scanning, but does not explicitly state when to prefer this tool over alternatives such as get_dex_spread or get_best_venue. Some guidance is implied by the scope (chain-wide vs. specific pair), but it is not explicit.

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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