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AI provider health reading (paid: 0.005 RLUSD / 0.005 USDC on Base / 0.005 RLUSD on Base via x402)

decide_provider_health
Read-only

Paid: 0.005 RLUSD per call via x402 on XRPL mainnet (xrpl:0), or 0.005 USDC on Base (eip155:8453). Pay per call, solves one question: What does this AI provider's status page and our last 24h record show? Raw indicator, incidents, and disturbed-check share with sources and timestamps. Without payment this returns isError with the x402 PaymentRequired object (fresh invoiceId); retry with the signed payload in _meta["x402/payment"] or the payment_signature argument. Unpaid calls cost nothing.

Input Schema

NameRequiredDescriptionDefault
providerYesVendor slug (status feeds: anthropic, morph; others return unknown) or a model id like anthropic/claude-sonnet-4
payment_signatureNoOptional. Base64 x402 PAYMENT-SIGNATURE value (signed RLUSD or USDC PaymentPayload) for hosts that cannot set _meta["x402/payment"]. Omit on the first call to receive the payment requirements.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / provider / description
      Previous value: -"Vendor slug (openai, anthropic, google, ...) or a model id like openai/gpt-4o"New value: +"Vendor slug (status feeds: anthropic, morph; others return unknown) or a model id like anthropic/claude-sonnet-4"
  2. Added

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the annotations, the description discloses pricing across two networks, the failure mode (isError plus a x402 PaymentRequired object with a fresh invoiceId), the retry mechanism, and the fact that a new invoiceId is issued per call, which helps the agent understand the non-idempotent behavior flagged by idempotentHint=false. It also says exactly what the successful payload contains, which annotations cannot convey.

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?

Three dense sentences with no filler; the payment contract, the question answered, the payload, and the error/retry path all appear in order. Minor waste comes from restating the price already present in the title, and leading with price rather than purpose makes the first sentence less agent-friendly than it could be.

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?

There is no output schema, and the description compensates by naming the returned fields and their provenance (sources and timestamps). Payment, error, and retry behavior are all covered, leaving nothing an agent needs in order to call this correctly and interpret the result.

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%, and both parameters are already well documented in-schema, including the vendor-slug-or-model-id duality and the Base64 PAYMENT-SIGNATURE alternative. The description repeats the payment mechanics but adds no new meaning about the provider parameter, so the baseline 3 applies.

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 scope: an AI provider's status page plus a 24h internal record, returning raw indicator, incidents, and disturbed-check share. That is far more concrete than the tool name alone, but it never distinguishes itself from adjacent siblings such as get_service_status, get_pulse_providers, or get_x402_health_report, so an agent cannot tell from the text which health tool to pick.

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 invocation contract is explicit: pay per call, omit payment on the first call to receive requirements, and retry with the signed payload in _meta["x402/payment"] or payment_signature. Unpaid calls cost nothing, which clarifies a low-risk path for discovery. The gap is that no alternative sibling tool is named as the right choice when this one is not what the agent needs.

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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