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AgentIndex — measured reliability for agent services

price_check

Price check. PRICED: $0.001 in USDC on base via x402 -- no account, no API key, no invoice. Call without payment to receive the exact payment requirements, then call again with payment to be served. What this endpoint charges as we last observed it, not as it advertises, with the live payment terms and whether they match the published ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesA domain, URL or indexed service id
paymentNoOptional. An x402 X-PAYMENT header value. Omit it to receive the payment requirements for this call; supply it to be served. Price: $0.001

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses the cost ($0.001 USDC on base via x402), the auth model (no account, no API key, no invoice), and the payment protocol flow. It stops short of stating rate limits, failure modes, or what happens if payment is rejected, which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The summary is front-loaded but the middle is a sprawling run-on sentence that packs protocol details, pricing, and two-call mechanics together. The content mostly earns its place, but the structure could be broken into clearer clauses.

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?

For a paid x402 endpoint with no output schema and no annotations, the description covers the essential context an agent needs: cost, auth model, the two-step payment handshake, and the nature of the returned data (live terms and whether they match published ones). Minor gaps remain around payment failure behavior.

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 `target` and `payment`, including the omit-vs-supply behavior and the price. The description restates that same mechanic rather than adding new meaning, so the baseline 3 is appropriate.

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 names the resource and states a specific scope: 'What this endpoint charges as we last observed it, not as it advertises, with the live payment terms and whether they match the published ones.' This distinguishes the observed-vs-advertised angle from siblings like get_service_report or payment_evidence, though it never names an alternative explicitly. The opening 'Price check.' is terse but the second sentence carries the real purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear invocation guidance for the two-call handshake ('Call without `payment` to receive the exact payment requirements, then call again with `payment` to be served'), which is genuinely useful. However, it offers no guidance on when to choose this over sibling tools such as payment_evidence, preflight_check, or cheapest_that_works, leaving the selection decision to inference.

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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