KeeSpecs

quote_convert_check

Read-only

Go, caution or no-go before a convert or bridge on Keeta. Not a quote or a guarantee. Returns the x402 payment quote for this read (price, network, asset, pay-to, and the exact URL). It does not return data. To buy, GET the returned URL over HTTP and pay with x402; check get_x402_health first.

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": {
      "kind": "<kind>",
      "amount": "<amount>"
    },
    "name": "quote_convert_check"
  }
}

Input Schema

Name	Required	Description
`to`	No	convert: token
`from`	No	convert: token
`kind`	Yes	convert or bridge
`token`	No	bridge: token
`amount`	Yes	Decimal size in whole tokens
`toChain`	No	bridge: destination chain

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 2, 2026

TDQS

A4.5/5.0

Behavior5/5

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

The annotations already mark it read-only and open-world, and the description adds critical behavior: it returns only an x402 payment quote, not data, and the actual result requires an external HTTP GET plus x402 payment. This clarifies the two-step payment workflow and avoids misinterpretation.

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?

The description is front-loaded with purpose, then quickly covers the not-a-quote caveat, return contents, no-data behavior, and the required next steps. Every sentence carries useful information with no filler.

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 the lack of an output schema, the description clearly lists what the returned payment quote contains (price, network, asset, pay-to, URL) and explains that the actual data must be purchased via x402. It also names the prerequisite health check, making the workflow complete enough for correct invocation.

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 description coverage is 100%, so the parameter meanings are already fully documented in the input schema. The description reinforces the convert/bridge context but does not add parameter-specific syntax, defaults, or constraints beyond the schema.

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 resource and scope: a preflight check before a convert or bridge on Keeta that returns an x402 payment quote rather than the actual data. It explicitly distinguishes itself from a quote or guarantee and explains the follow-up payment flow, so an agent can tell what it does and what it does not do.

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 clearly says to use this before a convert or bridge and to check get_x402_health first. It also explains the next step after receiving the quote: GET the returned URL over HTTP and pay with x402. It does not explicitly compare against other quote_* siblings, but the context is strong.

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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