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Focxle: virtual cards and spend limits for AI agents

budget_status

Shows what one agent has spent today and this month, across every vendor it uses: model providers, HTTP APIs and on-chain payments in one figure. Free, and needs no account if you already have a deployment id. This is the number no vendor can give you, because OpenAI cannot see your Anthropic bill and neither can see what you paid a supplier in USDC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deploymentNoThe deployment id to report on. Defaults to you, if you are a registered deployment.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses a read-only nature ('Shows'), cost ('Free'), and the unique aggregation behavior across vendors, including on-chain payments. It also clarifies account requirements. While it doesn't discuss potential errors or rate limits, the details given are useful for setting expectations.

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?

The description is three sentences, each serving a distinct purpose: defining the core function, stating cost and account requirements, and explaining why the tool's data is uniquely valuable. It is front-loaded with the main action and has no wasted words.

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?

For a simple read tool with one optional parameter and no output schema, the description covers the primary use case, prerequisites, and result format ('one figure'). It lacks explicit handling of error cases (e.g., invalid deployment id) but is otherwise sufficient for an agent to select and invoke the tool correctly.

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 description coverage is 100%, as the only parameter 'deployment' is described. The description adds meaningful context by explaining that a deployment id is sufficient even without an account, and defaults to you if registered. This enhances understanding of the parameter's role beyond the schema, though not extensively.

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 clearly states the tool's function with a specific verb ('Shows') and resource ('what one agent has spent today and this month'), and differentiates from siblings by emphasizing aggregation across all vendors (model providers, HTTP APIs, on-chain payments). This distinguishes it from budget_history or other budget tools that might focus on different time ranges or methods.

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 provides clear context for when to use the tool: to check today's and this month's spending across all vendors. It also mentions prerequisites ('needs no account if you already have a deployment id'). However, it does not explicitly contrast itself with alternatives like budget_history or budget_verify, so it misses an explicit when-not-to-use statement.

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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