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MoneyTools x402 agent toolkit

Transaction status + confirmations

tx_status
Read-onlyIdempotent

Is my transaction pending, confirmed, reverted or not found? Confirmations and a per-chain finality hint. Cheap polling for agents waiting on a tx. Free: 10 calls/day; then $0.001/call via x402 (MCP params._meta["x402/payment"] or HTTP) or X-API-Key credits. [served by tools.moneytools.dev]

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": {
      "chain": "<chain>",
      "hash": "<hash>"
    },
    "name": "tx_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
hashYes0x tx hash
chainYeschain: base, ethereum, arbitrum, optimism, polygon, bsc, avalanche

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, openWorld), and the description adds genuinely new behavioral facts: the free tier of 10 calls/day, the $0.001/call fallback, and the two payment paths (params._meta["x402/payment"] or X-API-Key credits). It also discloses the possible terminal states including "not found", which the annotations cannot express.

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?

It is front-loaded with the core question the tool answers, then layers confirmations, finality, use case, and pricing in descending importance. The pricing sentence is dense but earns its place for an agent that must decide whether it can afford to poll; the hosting tag is the only near-noise element.

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?

With an output schema present, the description need not explain return values, and it covers purpose, result states, cost/quota, and payment mechanics. An agent has everything needed to decide to call it and how to pay for it.

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?

Both parameters are fully documented in the schema (100% coverage), including a hash example and the supported chain list, so the schema carries the semantics. The description adds nothing about parameter formatting or behavior, which is acceptable given the coverage baseline.

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 states a specific resource and the exact answer shape: pending / confirmed / reverted / not found, plus confirmations and a per-chain finality hint. That is far more concrete than a restatement of the name. It does not explicitly name the sibling tx_explain or contrast itself with it, so sibling differentiation is left implicit.

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?

"Cheap polling for agents waiting on a tx" gives a clear context for when to reach for this tool rather than an explanation/deep-inspection tool. There are no explicit when-not conditions or named alternatives, but the intended use case is unambiguous.

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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