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alphapipeline

dex.liquidity_slippage

Read-only

Use this tool to calculate expected DEX price slippage, pool liquidity depth, and optimal routing before executing an on-chain token swap. GeckoTerminal-backed pool analytics with constant-product slippage estimation for the requested trade_size_usd, plus a slippage_tiers array with the same estimate at fixed $1,000/$5,000/$10,000 sizes so an agent can gauge depth at a glance without extra calls. Do not use for centralized exchange (CEX) orderbooks or contract risk analysis. Paid in USDC on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
networkNoGeckoTerminal network id, e.g. base, eth. Defaults to base.
pool_addressNoSpecific DEX pool contract address (optional if token_address is given).
token_addressNoToken contract address - the most liquid pool is auto-selected (optional if pool_address is given).
trade_size_usdYesHypothetical trade size in USD to estimate slippage for.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noticeNo
networkYes
pool_nameNo
data_sourceYes
generated_atYes
pool_addressNo
liquidity_usdNo
token_addressNo
slippage_tiersNo
trade_size_usdYes
volume_24h_usdNo
price_impact_modelYes
estimated_slippage_pctNo

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and destructiveHint. The description adds no additional side-effect information beyond the implied non-mutating 'calculate' action, so it meets the baseline for annotated tools without extra context.

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 concise, with three sentences that pack key information: purpose, use case, exclusions, and output highlights. No fluff or redundancy.

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

Completeness5/5

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

For a read-only analytics tool with 4 parameters and an output schema, the description provides all necessary context: what it calculates, when to use it, what to avoid, and a hint at the output structure (slippage_tiers). Nothing essential is missing.

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 descriptions cover all parameters at 100%. The tool description reiterates the optionality between pool_address and token_address and the auto-selection logic, but this is already present in the schema, so it adds minimal new semantic value.

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 calculates DEX price slippage, pool liquidity depth, and optimal routing, with a specific verb and resource. It distinguishes itself from sibling tools by focusing on pre-swap analysis and explicitly excluding CEX and contract risk.

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

Usage Guidelines5/5

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

It explicitly says when to use the tool (before executing an on-chain token swap) and when not to use it (CEX orderbooks, contract risk analysis). This provides unambiguous guidance on applicability.

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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