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Aether: Base onchain data & token risk (x402)

audit_x402_payability

Read-only

x402 Payability Audit: probes an x402 endpoint and checks its 402 challenge (CAIP-2 network, canonical USDC asset, payTo checksum, amount, EIP-712 domain, resource URL, Bazaar discovery) with a fix for every failure. Price: $0.01 USDC on Base via x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic https URL of the paid x402 endpoint to audit
bodyNoExample JSON body the endpoint accepts
expectNoWhat the paying caller needs: fails the audit if the endpoint cannot be paid this way
methodNoDefaults to POST when body is supplied, otherwise GET
headersNoNon-credential headers the endpoint needs before its paywall (e.g. Idempotency-Key)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, but the description adds a genuinely load-bearing trait they don't cover: this is a paid call costing $0.01 USDC on Base via x402, and it returns a fix for every failure. That cost disclosure is exactly the kind of context an agent needs before invoking. It stops short of noting rate limits or result structure.

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?

Two sentences, front-loaded with the tool's identity and check list, with the price disclosed last. It is dense but every clause (the enumerated checks, the fix guarantee, the cost) earns its place; no filler.

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?

No output schema exists, so the description carries return-value burden, and it does so partially by enumerating the checks and promising a fix per failure. Given the rich 5-parameter schema and read-only/open-world annotations, an agent has enough to call it, though result formatting and failure-report shape remain unstated.

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 url, body, expect, method, and headers with defaults and constraints. The description adds no per-parameter syntax or format guidance beyond the general 'probes an x402 endpoint' framing, so the baseline of 3 applies.

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?

States a specific verb (probes/checks) and resource (an x402 endpoint's 402 challenge) and enumerates exactly what it inspects — CAIP-2 network, USDC asset, payTo checksum, amount, EIP-712 domain, resource URL, Bazaar discovery. This is far more specific than any sibling and an agent can distinguish it from audit_evidence or score_opportunity immediately.

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?

Usage is implied — you audit an x402 endpoint to verify it is payable before integrating or paying — and 'with a fix for every failure' hints at the remediation value. But it never names when to prefer this over siblings (audit_evidence, score_opportunity) or states preconditions/exclusions explicitly.

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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