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get_x402_scaffold

EIP-712 integration scaffold + live failure diagnostics for the AgentPay x402 facilitator (invention #4240). With stats=False, returns the single-file integration scaffold (lang 'py' or 'go') with the EXACT AgentPay EIP-712 domain and types, a known-good self-test vector, and its unique scaffold_id — run the code offline with --self-test to validate your environment before paying on mainnet. With stats=True, returns the live /verify failure-code distribution (14d) and the scaffold users' first-time success rate. Free to call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNopy
statsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that it returns a scaffold and optionally stats, mentions 'Free to call' (cost transparency), and warns to run self-test before paying. It does not explicitly state that it has no side effects, but the read-only nature is implied by 'returns.' The description is transparent about its two modes and their outputs.

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?

The description is dense but well-structured, leading with the main purpose and then breaking down the two modes. It avoids unnecessary fluff and each clause adds value. It could be slightly more concise but remains efficient and front-loaded.

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?

Given an output schema exists and the tool has two parameters with clear behavior, the description is complete. It explains what the tool does, how to use it, what parameters mean, and provides a practical usage tip (self-test). There is nothing an agent needs to know to call it correctly that is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It fully explains both parameters: 'lang' is described as 'py' or 'go' (the supported values), and 'stats' is explained with the exact behavior of True/False. This is excellent compensation for the lack of schema descriptions.

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?

The description states a specific verb ('returns') and resource (EIP-712 integration scaffold + live failure diagnostics) with clear differentiation between the two modes (stats=False vs stats=True). It names the exact domain and purpose (AgentPay x402 facilitator) and even references an invention number, making it unambiguous and distinct from sibling tools.

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 description gives clear instructions on how to use the returned scaffold ('run the code offline with --self-test to validate your environment before paying on mainnet') and notes 'Free to call.' It explains the two modes but does not explicitly mention alternatives or when not to use it, though the purpose is clear enough that an agent can decide.

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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