Skip to main content
Glama
Spicy-API
by Spicy-API

Get current SpicyAPI key usage

spicyapi_usage_get
Read-onlyIdempotent

Retrieve settled USD spend and task counts grouped by day and model for your API key, using a date range to generate usage reports.

Instructions

Read task counts and settled actual USD spend for the current API key, grouped by creation day and model. Only from/to dates are accepted: UTC [from,to), at most 92 days; defaults to seven days ending tomorrow UTC. Money is returned as exact decimal strings; pending holds are excluded and late settlement can change prior-day spend. This is not account balance or remaining key budget, and is not a generation prerequisite. Use for requested usage reports; respect Retry-After on rate limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoExclusive UTC date, YYYY-MM-DD. Defaults to tomorrow UTC.
fromNoInclusive UTC date, YYYY-MM-DD. Defaults to seven days before to.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.5

TDQS

A4.9/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true and idempotentHint=true, but the description adds unique behavioral context: money is returned as exact decimal strings, pending holds are excluded, late settlement can change prior-day spend, and rate limits should respect Retry-After. These details go beyond annotations and help the agent understand the reliability and semantics of the data.

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?

Every sentence carries weight: purpose, constraints, return format, exclusions, boundary clarification, and usage guidance. The most critical information (what it does and what it is not) is front-loaded. No redundancy or filler.

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 the tool's simplicity (2 optional parameters, read-only, idempotent) and that an output schema exists, the description covers all essential operational details: defaults, date range cap, return format, and exclusions. It is complete for an agent to call 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 coverage is 100% (both parameters have descriptions), so the baseline is 3. The description adds interval semantics (UTC [from,to), at most 92 days, defaults) which is useful beyond the schema. It doesn't dive into each parameter individually, but the added context justifies a 4 rather than a baseline 3.

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 begins with a specific verb+resource: 'Read task counts and settled actual USD spend for the current API key, grouped by creation day and model.' It explicitly distinguishes itself from siblings by stating it is not account balance or remaining key budget, and not a generation prerequisite. This leaves no ambiguity about what the tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit use case: 'Use for requested usage reports.' It also states what it is not (balance, budget, generation prerequisite), effectively telling the agent when not to use it. This is sufficient guidance for selecting between siblings like balance_get.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.