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Screen a payment before paying

screen_payment
Read-only

Screens a payment counterparty before you pay, checking address sanity, dynamic payTo swaps, transport safety, and your spending policy. Returns allow, review, or block with reasons.

Instructions

Screen a counterparty an agent is about to pay. Runs entirely offline: address sanity, dynamic-payTo comparison, transport check, and your spending policy. Returns allow / review / block with reasons. Advisory: the caller decides. Set FRISK_API_KEY to add hosted reputation signals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetNoAsset symbol, e.g. USDC.
amountNoAmount the agent is about to pay.
endpointNoURL that quoted the payment. Used to check transport safety.
maxPerCallNoSpending ceiling for a single call.
strictnessNo0 is permissive, 1 is paranoid. Defaults to 0.3.
counterpartyYesThe address the agent intends to pay, e.g. an 0x EVM address.
allowedAssetsNoAssets the agent is permitted to pay in.
observedPayToNoThe payTo address the endpoint actually returned for this request. If it differs from the counterparty, that is the dynamic-payTo swap.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.0.1

TDQS

A4.7/5.0
Behavior5/5

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

Discloses that it runs offline, returns a recommendation with reasons, leaves the final decision to the caller, and notes the optional FRISK_API_KEY for hosted signals. This goes beyond the annotations and fully describes behavior.

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

Conciseness5/5

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

Two concise sentences that convey purpose, behavior, and optional configuration without any redundant or tangential information.

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 no output schema, the description explicitly names the return categories (allow/review/block with reasons) and clarifies that it is advisory and offline, covering all essential context an agent needs.

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

Parameters4/5

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

Schema covers all 8 parameters with clear descriptions. The description adds relational context (e.g., dynamic-payTo comparison between observedPayTo and counterparty, spending policy tied to allowedAssets/maxPerCall/strictness), enhancing the schema's meaning.

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?

Clearly states the action (screen), the object (counterparty about to be paid), and the outcome (allow/review/block with reasons). No ambiguity about the tool's purpose.

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?

Implies when to use (before paying) and provides operational context (runs entirely offline, advisory only). Does not explicitly contrast with alternatives, but no sibling tools are present.

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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