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Focxle: virtual cards, spend limits and procurement for AI agents

payment_record

Submit a receipt or invoice for a payment you already made, on ANY platform, so it counts towards your record. Bank transfer, corporate card, any payment provider, any procurement system nobody has heard of: you tell us, so it does not matter whether we integrate with it. Each payment moves your score. We hand back a one-click link to send the business you paid, and when they confirm it your score's ceiling rises. Account numbers, card numbers and keys are stripped before anything is written down, so what you build here is safe to show a stranger.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
atNoRFC3339 time of the payment. Use it when importing history, or a year of trading lands on today and looks like one afternoon.
noteNoAnything worth remembering.
payeeYes
amountYes
intentNoWhat it was for.
platformNoWhere you paid: "stripe", "bank_transfer", "corporate_card", anything. A record spanning several platforms is worth more to a reader.
external_refNoYour own invoice or transaction reference.
idempotency_keyYesRequired. Your own id for this payment, so a retried import never records it twice.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure, and it does well: it reveals that account numbers, card numbers, and keys are stripped before persistence, that each payment affects the user's score, and that a confirmation link is returned for the payee. It does not mention rate limits or authorization, but the data-handling and scoring side effects are clearly stated.

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 front-loaded with the core purpose and then uses each subsequent sentence to add a distinct piece of behavioral context: platform flexibility, score impact, confirmation workflow, and data scrubbing. It is slightly wordy in the 'any procurement system nobody has heard of' phrase, but no sentence is wasted.

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?

The tool has 8 parameters, nested objects, no output schema, and no annotations, yet the description supplies enough operational context to call it correctly: what counts as a valid submission, how platform is handled, the confirmation flow, and privacy safeguards. It only partially describes the return value (one-click link, ceiling rise), but the essential invocation context is present.

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 coverage is 75%, so the baseline is 3. The description reinforces the purposeful use of platform and external references ('any payment provider', 'you tell us') and warns against sensitive identifiers, but it does not add substantial parameter-level semantics beyond the schema's own 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 opens with a specific verb and resource: 'Submit a receipt or invoice for a payment you already made' and clarifies the cross-platform scope. This clearly distinguishes it from siblings like payment_history_mine (reading history), spend_request_approval (approving before spending), and card_get_virtual (issuing cards).

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 a clear trigger: use this for payments already made on any platform, regardless of integration. It does not explicitly name sibling alternatives or give 'when not to use' exclusions, so it stops short of a 5, but the context is unambiguous for an agent choosing among the listed siblings.

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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