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Pre-flight: AI provider conditions (paid: 0.001 RLUSD or 0.001 USDC on Base via x402)

decide_provider_health
Read-only

Paid: 0.001 RLUSD per call via x402 on XRPL mainnet (xrpl:0), or 0.001 USDC on Base (eip155:8453). Use when an agent is about to call an AI provider and wants a pre-flight conditions reading. Returns a reading (go = operational, caution = minor or maintenance, no_go = major or critical, unknown = no reading) and a handling flag derived from it, from the vendor's own public status page (credited per source; not affiliated), with the disturbed share of checks over 24h. openai, cursor, cohere, perplexity, inference-net and amazon are no longer measured (status null until 2026-11-12). 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

TableJSON 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?

Goes well beyond the readOnlyHint/openWorldHint annotations: it discloses exact pricing (0.001 RLUSD on XRPL or 0.001 USDC on Base), the failed-call behavior (isError with a fresh x402 PaymentRequired invoiceId), the retry paths (_meta["x402/payment"] or payment_signature), the meaning of each reading value, and the unrouted providers whose status is null until 2026-11-12. This is rich, decision-relevant disclosure that an agent could not derive from the schema.

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?

Front-loads the payment cost first, then usage, return values, deprecation status, and failure handling. Every sentence carries information, though the payment bootstrapping details and the return-value enumeration make it dense relative to a two-parameter tool.

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, so the description must explain returns — and it does, enumerating go/caution/no_go/unknown, the derived handling flag, and the 24h disturbed-check share. Combined with the payment failure/retry flow and the null-status provider list, an agent has everything needed to call and interpret this correctly.

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 schema already documents both parameters well, including the vendor-slug/model-id formats and the payment_signature role. The description adds little parameter-level detail beyond echoing the payment_signature/x402 mechanics, so it sits at the documented 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 verb and resource: a 'pre-flight conditions reading' of AI provider health from vendor status pages. It is clear what the tool does, but it never names or contrasts the near-siblings get_service_status, get_current_conditions, or get_pulse_providers, so an agent must infer the split itself.

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?

'Use when an agent is about to call an AI provider and wants a pre-flight conditions reading' gives a concrete triggering context. However, it offers no when-not guidance and no named alternative for cases where a different status tool would be the right pick.

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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