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Get spend & budget

get_usage
Read-only

Get the account's AI spend and budget: how much has been spent this billing period, the plan's included credits, any budget cap, and whether new tasks are blocked (with the reason). Call this before a long series of prompts to check remaining budget, since dispatch fails once a spend ceiling is reached. Only agent runs stop: write_file, exec, start_app and deploy keep working, so the code can still be written and run by hand.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
planNoThe account's plan.
reasonNoWhy tasks are blocked: budget_cap, credits_exhausted, or ai_disabled (agent tasks turned off for this account).
blockedYesWhether new tasks are refused right now.
serversNoServers on the account.
projectsNoProjects on the account.
bonus_usdNoRemaining one-time welcome credit, in USD.
spend_usdNoAI spend this billing period, in USD.
budget_cap_usdNoYour own budget cap, or null when none is set.
hard_limit_usdNoThe lowest ceiling that blocks new tasks, or null.
overage_allowedNoWhether the plan allows billable spend past its credits.
included_credits_usdNoAI credits the plan includes, in USD.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered; the description goes well beyond that by disclosing the failure mode (dispatch fails at the ceiling) and precisely which operations are blocked versus unaffected. That is exactly the kind of operational context annotations cannot express.

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?

Three sentences, front-loaded with what is returned, then the when-to-call guidance, then the blast-radius detail. Every sentence carries information, though the trailing list of unaffected tools is slightly verbose relative to the core message.

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?

With an output schema present, return shape needn't be re-explained, and the description still covers the operational semantics an agent needs: when to call, why it matters, and what breaks versus what keeps working. Nothing material is missing for a zero-parameter read tool.

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 tool takes no parameters, so the baseline is 4 and there is nothing for the description to disambiguate. The enumerated output fields are a bonus that helps the agent interpret results, though the output schema already covers them.

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?

States a specific verb and resource ('Get the account's AI spend and budget') and then enumerates exactly what is returned: spend this period, included credits, budget cap, and blocked status with reason. No sibling tool in the list touches billing or budget, so the agent can route here unambiguously.

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?

Gives an explicit trigger ('Call this before a long series of prompts to check remaining budget') and the reason ('dispatch fails once a spend ceiling is reached'). It also scopes the consequence — only agent runs stop, while write_file, exec, start_app and deploy keep working — so the agent knows when the check matters and when it does not.

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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