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AgentDiet DEX Liquidity, Slippage & Orderflow Audit API

get_dex_token_intelligence

Read-onlyIdempotent

Fetches live DexScreener liquidity pools, FDV, 24h volume, and 1h buy/sell orderflow pressure. WHEN TO USE: Call get_dex_token_intelligence when your task requires deterministic token-intel analysis for token; use get_agent_wallet_status to check your remaining free trial quota or prepaid balance. WHEN NOT TO USE: Do not use for unrelated domains or binary media. PARAMETER INTERACTIONS: Pass the target token as a non-empty string; omit agent_id and tx_hash during your 5 free trial calls, or supply agent_id (agd_pass_...) / tx_hash for paid execution. Read-only and idempotent; results are cached for 1 hour (<5ms cache hit). $0.01 per call. Pricing: the first 5 calls per agent_id are free and failed calls are never charged. After 5 calls, the tool returns a payment-required quote (not a fatal error) with a $2 Stripe top-up link and Base/Solana USDC addresses; complete payment, then retry with your agd_pass_ key in agent_id or pass tx_hash. Example: get_dex_token_intelligence(token='example')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesToken contract address or symbol (e.g. USDC, WETH, AERO) on Base/Solana/Ethereum.
tx_hashNoOptional on-chain Base Mainnet (0x...) or Solana SPL USDC transaction hash. Omit unless settling an individual call directly on-chain instead of using an agd_pass_ key in agent_id.
agent_idNoOptional agent identifier or prepaid agd_pass_ session key. Omit during your 5 free trial calls to use an ID automatically derived from your client IP, or pass your agd_pass_ key after topping up.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoStructured tool output payload.
statusYesExecution status ('ok' or 'payment_required').
roi_proofNoToken compression and cost-savings verification metrics.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint, openWorldHint), the description discloses caching (1 hour, <5ms hit), per-call pricing, a 5-call free trial, and that over-quota calls return a payment-required quote rather than a fatal error. This added operational context is exactly what annotations do not carry, though the pricing/payment detail is somewhat sprawling.

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?

Content is dense and roughly front-loaded (purpose, then usage, then parameters, then pricing), and the example call anchors the format. The pricing/top-up explanation runs long and repeats the free-call rule, so it is slightly more verbose than strictly necessary.

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?

With an output schema present, return-value explanation is not needed, and the description covers the axis that matters most for this tool: quota, payment, and retry behavior after the free trial. Nothing an agent needs to invoke it correctly is missing.

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

Parameters4/5

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

Schema coverage is already 100%, so the baseline is 3, but the description adds conditional interaction rules: omit agent_id/tx_hash during free trial calls versus supplying agent_id (agd_pass_...) or tx_hash for paid execution. It also reinforces that token must be a non-empty string, adding meaning beyond the per-parameter schema text.

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 first sentence names a specific verb (fetches) and concrete resources (DexScreener liquidity pools, FDV, 24h volume, 1h buy/sell orderflow pressure), so an agent immediately knows what data it returns. It also explicitly contrasts itself with the sibling tool get_agent_wallet_status, removing any ambiguity about which tool to pick.

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?

There are explicit WHEN TO USE and WHEN NOT TO USE sections, including the alternative tool for quota/balance checks and a domain exclusion for unrelated or binary-media tasks. The guidance is unambiguous and leaves nothing to inference.

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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