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APEX Runner Crypto Signals

slippage_forecast

$0.007 — Call this before any order above a few hundred dollars so you don't pay hidden market impact — returns expected slippage % and USD cost for your coin, size_usd and side, and tells you EXECUTE_NOW, EXECUTE, SPLIT_ORDER (with a tranche count) or USE_LIMIT. Params: coin=BTC, size_usd=5000, side=buy

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "slippage_forecast"
  }
}

Input Schema

NameRequiredDescriptionDefault
coinNoCryptocurrency symbol (default: BTC)BTC
sideNoOrder side (default: buy)buy
size_usdNoOrder size in USD, 10-1000000 (default: 1000)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations supplied, the description carries the full burden, and it does disclose useful behavior: a $0.007 cost, the two returned metrics, and the four decision categories including SPLIT_ORDER with a tranche count. It does not state latency, rate limits, or whether the forecast assumes a specific order type, and it is silent on failure modes for out-of-range sizes.

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 price, the usage trigger, and the return contract are packed into one front-loaded sentence, with params appended compactly. It is dense but every clause carries information; only the param echo at the end is arguably redundant with the schema.

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

Completeness4/5

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

For a three-param, read-only forecasting tool with no output schema and no annotations, the description supplies the return shape (slippage % and USD cost) and the decision vocabulary an agent needs to interpret results. Coverage is good; only operational details such as latency or data freshness are absent.

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%, with enums and min/max already documenting every field, so the baseline is 3. The description only restates the three parameter names and supplies example values (coin=BTC, size_usd=5000, side=buy), which adds no meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete action and its result: it returns expected slippage % and USD cost for a given coin/size/side, and produces an execution recommendation. That is far more specific than the tool name alone. It does not, however, contrast itself with plausible siblings like execution_window_optimizer, so it stops short of a 5.

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?

It gives an explicit trigger condition: call this before any order above a few hundred dollars to avoid hidden market impact. That is clear situational guidance. It lacks explicit when-not-to-use guidance or a named alternative for small orders or for execution-timing questions.

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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