AIKIT by Trading Checkup

Exchange facts with sources

venue_facts

Read-onlyIdempotent

1 credit. Returns verified exchange/broker facts a trading bot depends on: fee tiers, API rate limits, error codes and what they mean, testnet/demo settings. Each fact has value, unit, official source URL, date read and a signed receipt. Use it when writing or fixing bot code that must respect a venue's limits, instead of guessing numbers.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "venue": "<venue>"
    },
    "name": "venue_facts"
  }
}

Input Schema

Name	Required	Description
`topic`	No
`venue`	Yes	okx, binance, bybit, kraken, coinbase, bitget, ibkr or mt5
`market`	No
`symbol`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 15, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare read-only, idempotent, closed-world and non-destructive, so safety is covered. The description adds genuinely new behavioral context: a 1-credit cost, and the provenance attached to each returned fact (value, unit, official source URL, date read, signed receipt), which tells the agent the data is sourced and verifiable.

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?

Three tight sentences, front-loaded with the credit cost, then content, then the decision rule. The sentence describing the returned fact structure earns its place since there is no output 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?

With no output schema, the description appropriately describes the return shape and provenance. The main remaining gap is the undocumented market/symbol parameters, a minor omission for a read-only lookup tool with full annotation coverage.

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 only 25% across four parameters. The description partially compensates by mapping the kind of facts returned (fees, limits, errors, testnet), which aligns with the topic enum, but it says nothing about the market, symbol, or venue parameters' semantics or interactions.

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?

States a specific verb and resource ('Returns verified exchange/broker facts') and enumerates the exact facts covered: fee tiers, API rate limits, error codes, testnet/demo settings. It does not explicitly differentiate itself from siblings like symbol_spec or prop_rules, which share overlapping subject matter (symbols appear in the topic enum here), 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?

Gives a concrete usage trigger: 'Use it when writing or fixing bot code that must respect a venue's limits, instead of guessing numbers.' This clearly frames the situation, but offers no when-not conditions or named alternative for cases like single-symbol specs.

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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