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ymylive
by ymylive

get_dex_pair

Get comprehensive details of a specific DEX pair on a blockchain, including transaction counts, price changes, liquidity, and social links.

Instructions

Get full detail for a single DEX pair on a specific chain.

Use after dex_search / get_dex_token_pairs when the user wants the full picture for one specific market — including buy/sell tx counts at multiple windows (m5/h1/h6/h24), price changes, native-token price, base/quote liquidity sides, and links/socials when present.

Args: chain_id: Chain identifier as DexScreener returns it. Typical values: "ethereum", "bsc", "solana", "polygon", "arbitrum", "base", "optimism", "avalanche", "pulsechain", "fantom", "cronos", ... pair_address: The pair's contract address (case-insensitive on EVM).

Returns: The first matching pair object as returned by DexScreener (with the full txns, info, volume, priceChange, liquidity sub-objects), or {"error": "pair not found"} if no pair matches, or the structured HTTP error dict on transport failure.

Note: chain_id is validated against ^[a-z0-9-]{1,32}$ and pair_address against EVM hex / Solana base58.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chain_idYes
pair_addressYes
Behavior4/5

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

No annotations provided, so the description carries full burden. It details the return value structure, including sub-objects and error cases, and notes input validation. It does not discuss rate limits or authentication, but for a read operation these are acceptable omissions.

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 well-structured with a clear intro, Args, and Returns sections. It is concise yet complete, with every sentence adding value. Front-loaded with purpose.

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 simple two-parameter tool with no annotations or output schema, the description covers all necessary aspects: purpose, usage context, parameter details, return format (including error cases), and validation. It is self-contained and comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description compensates thoroughly: it explains chain_id with typical values and pair_address with case-insensitivity, and mentions validation regex patterns. This adds significant meaning beyond the 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?

The description clearly states the tool gets full details for a single DEX pair on a specific chain, with explicit mention of what information is included (tx counts, price changes, liquidity). It distinguishes itself from siblings like dex_search and get_dex_token_pairs by indicating it is for a single pair.

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 explicitly says 'Use after dex_search / get_dex_token_pairs when the user wants the full picture for one specific market', providing clear guidance on when to invoke this tool. It does not mention when not to use it, but the context is sufficient.

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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