ensotrade

Leg Rates

leg_rates

What it costs, right now, to move USD into and back out of the stablecoins the crypto venues quote in — and how much can be moved before the book runs out. Use for "what does USDT conversion cost", "is USDC or USDT cheaper to hold", "how much can I convert at once", "what is the USDT basis".

No coin involved: this is the currency leg on its own. Returns per-market cost in and out, the cheapest venue for each direction, aggregate capacity, and how far each stablecoin is trading from 1.0000.

where_to_convert IS THE ACTIONABLE PART: the cheapest and dearest conversion venue and the bp/USD penalty between them. Measured at 13.5x-17x on USDT and 27.7x on USDC, and the winner ROTATES with size because these books are shallow enough that the usual winner runs out — Kraken wins to $2.5M and loses to Bitfinex at $5M.

CAPACITY IS THE PART THAT SURPRISES PEOPLE. The USD/stablecoin books are thin relative to the coin books they feed, so a size that walks a coin book comfortably can exhaust the currency book outright. size_exceeds_capacity is a hard wall, not a cost.

par_offset_bp is NOT charged as a cost — a desk that buys and later sells the same stablecoin is flat to it. Do not add it to the round-trip figure.

notional_usd = the size to price. Requires an EnsoTrade Pro API key.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`notional_usd`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.6/5.0

Behavior5/5

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

With no annotations, the description carries full burden. It discloses key behavioral traits: capacity is a hard wall, par_offset_bp is not a cost, the winner rotates with size, books are shallow, and a Pro API key is required. These are non-obvious and essential facts not inferable from the schema.

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 longer than average but every section adds distinct value: use cases, capacity caveat, par_offset clarification, and parameter definition. It is front-loaded with the key question it answers. Slight verbosity in all-caps headings does not detract significantly.

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?

Given a single parameter, no annotations, and an output schema (which covers return structure), the description covers all necessary operational context: what is returned, how to interpret warnings, what not to add, and access requirements. An agent can call this tool correctly with high confidence.

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?

Only one optional parameter exists with 0% schema description coverage. The description explicitly defines notional_usd as 'the size to price' and mentions default sizing context (measured at certain multiples). This directly compensates for the schema's lack of description, though units and range are not detailed.

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 states a specific purpose: reporting costs to move USD into and back out of stablecoins, with per-market costs, cheapest venue, capacity, and deviation from $1.0000. It explicitly says 'No coin involved: this is the currency leg on its own,' which distinguishes it from sibling tools like carry_pressure or market_snapshot.

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 provides clear usage scenarios ('Use for...') and explicitly scopes the tool to the currency leg, implying it is not for coin-related queries. It does not explicitly list exclusions or alternatives, but the context signals are strong enough for an agent to route correctly.

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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TDQS

A3.8/5.0

Disambiguation4/5

Most tools target distinct analytics functions (order flow, execution cost, strategy testing, market scans). A few pairs overlap—mass_map/mass_scan, market_rotation/top_movers, and market_snapshot/perp_dashboard—but descriptions clarify differences. No tools are truly indistinguishable.

Naming Consistency3/5

Naming style is mixed: some tools use verb+noun (explain_move, fetch_series, get_funding) while others use descriptive noun phrases (carry_pressure, currency_leg, exit_capacity). The names are readable and meaningful, but the pattern is not uniform. It is not chaotic, but lacks a single consistent convention.

Tool Count4/5

22 tools is on the heavier side but reasonable for a comprehensive crypto analytics suite covering market data, execution analysis, risk, and strategy testing. Each tool serves a distinct purpose and contributes to the overall scope. It is not excessive enough to feel bloated.

Completeness5/5

The tool set covers the full analytics lifecycle: market overview, order-flow explanation, execution routing and cost, position limits, options, and strategy backtesting. There are no obvious dead ends; users can research, test, and validate strategies. The coverage is thorough for the stated trading-analytics domain.

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