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

spend_request_approval

Ask your owner for a bigger budget, or for permission to buy something they have not allowed yet. Returns a link to send them plus the words to send with it. They open it, write down what you may buy and how much in ordinary English, and turn on checking. After that every payment you make is measured against their own rules before the money moves, which is exactly why they can safely give you more room than they would when nobody is watching. The page asks them for no password and no bank details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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?

No annotations are provided, so the description carries the full burden. It discloses the flow (returns a link and words to send), the owner's process (writing rules in plain English), and security reassurances (no password or bank details). However, it does not mention potential failures (e.g., approval being denied) or side effects beyond the request creation, so it is thorough but not exhaustive.

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 a single paragraph that is front-loaded with the core purpose and then explains the process. It is efficient, with no redundancy, and every sentence contributes to understanding the tool's functionality and safety. It is slightly longer than necessary but remains readable and well-structured.

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 description explains the return value (a link and words), the owner's interaction, and the ongoing enforcement of rules. It covers the essential aspects for an agent to invoke the tool correctly. However, it does not address edge cases like what happens if the owner rejects the request or how to interpret the response, which would be useful but not critical given the tool's simplicity.

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?

The input schema has zero parameters, so the description does not need to explain parameter semantics. The baseline for 0 params is 4, and the description adds context about what the tool achieves without needing parameter details. It appropriately focuses on behavior rather than parameters.

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 ('Ask your owner') and resource ('bigger budget' or 'permission to buy something they have not allowed yet'). It clearly distinguishes itself from sibling tools like budget_request_increase by covering both budget increases and approval for unallowed purchases, and it describes the expected outcome (link and words to send). The purpose is unambiguous and actionable.

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?

The description clearly indicates when to use the tool (when you need budget or permission for an unallowed purchase), but it does not mention any alternatives or explicitly state when not to use it. While the context is clear, it lacks exclusions or comparisons to sibling tools like budget_request_increase, leaving some ambiguity about edge cases.

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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