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get_budget_gate

Retrieve runtime budget gate settings and current monthly LLM spend to check headroom and enforce mode for your LLM usage caps.

Instructions

Get the runtime budget gate settings (runtime control plane Phase 1) plus this month's LLM spend. Response = { gates: [{ id, projectId, monthlyLimitUsd, enforceMode, enabled, ... }], spentUsdThisMonth, monthStart, ttlSeconds }. monthStart is the UTC month start. The same source the SDK's budgetGate opt-in evaluates before execution. Distinct from get_llm_budget (which caps Argosvix's internal AI feature costs) — this one is a monthly cap on your own LLM spend. Example phrasing: "how much budget gate headroom is left this month?" / "is the gate set to fail_open?"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the returned fields (gates, spentUsdThisMonth, monthStart, ttlSeconds) and notes that monthStart is UTC. It also mentions the tool's relationship to the SDK's budgetGate opt-in. Lacks details on freshness/caching or authorization, but is fairly transparent.

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 concisely structured: first sentence summarizes purpose, then response format, then contextual details, then differentiation, then example queries. Every sentence adds value without redundancy.

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?

Given no output schema, the description sufficiently explains the response fields and behavior. It covers the core functionality and distinguishes from related tools. Could potentially mention if multiple gates are expected, but overall it is complete for a straightforward retrieval tool.

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

Parameters5/5

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

There are zero parameters, and the description appropriately indicates no inputs are needed. Schema coverage is 100% (empty schema), so no additional parameter details are required.

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 retrieves budget gate settings and monthly LLM spend. It specifies the response structure and explicitly distinguishes from the sibling get_llm_budget tool, making the purpose unambiguous.

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 explains when to use this tool ('how much budget gate headroom is left this month?') and distinguishes it from get_llm_budget. It could be improved by explicitly stating scenarios where it should not be used, but the distinction and examples are helpful.

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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