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romudille-bit

AgentPay x402 — Economic-intelligence layer for AI Agents

orderbook_depth

Estimate slippage and market depth for large trades up to $250k by retrieving real bid/ask spreads and per-exchange best prices for any trading pair.

Instructions

Get real bid/ask depth and slippage estimates at $10k, $50k, and $250k notional for a trading pair. Returns best bid/ask, spread percentage, and how much slippage to expect at each trade size.

Use when: You need to estimate slippage before executing a large trade. Tells you how much a $10k, $50k, or $250k order will move the market. Returns: best_bid, best_ask, spread_pct, depth with slippage_pct at $10k/$50k/$250k notional, per-exchange best prices Example response: {"asset": "ETH", "pair": "ETH/USDT", "best_ask": 2071.5, "best_bid": 2071.2, "spread_pct": 0.0145, "depth": [{"notional_usd": 10000, "slippage_pct": 0.002, "executable": true}, {"notional_usd": 50000, "slippage_pct": 0.008, "executable": true}, {"notional_usd": 250000, "slippage_pct": 0.031, "executable": true}], "exchanges": [{"exchange": "Binance", "best_ask": 2071.5, "best_bid": 2071.2}, {"exchange": "Bybit", "best_ask": 2071.6, "best_bid": 2071.1}], "source": "binance/bybit"}

Price: $0.000 USDC per call

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesTrading pair, e.g. ETHUSDT or BTCUSDT
exchangeNoExchange to query: binance (default) or bybitbinance
Behavior5/5

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

No annotations provided, but the description fully discloses the output structure, including best bid/ask, spread, depth with slippage at three notional sizes, per-exchange prices, and pricing per call. No side effects or destructive behavior implied.

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?

Well-structured with a clear first sentence, use case, return format, and example. Slightly lengthy but every sentence adds value. Could be slightly more condensed.

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?

No output schema, but the description explains the return structure thoroughly with an example. Covers important aspects like slippage at specific trade sizes and per-exchange data.

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 coverage is 100%, so baseline is 3. The description does not add significant meaning beyond the schema for symbol and exchange, though it contextualizes the purpose.

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 it gets real bid/ask depth and slippage estimates at specific notional sizes for a trading pair. It distinguishes well from sibling tools like fear_greed_index or crypto_news.

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?

Explicitly says 'Use when: You need to estimate slippage before executing a large trade.' Provides clear context but does not mention when not to use or alternatives.

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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