Check current API and resource usage vs plan limits: API calls, SMS credits, email credits, LLM calls remaining.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| apiCalls | No | {used, limit, remaining} | |
| llmCalls | No | {used, limit, remaining} | |
| smsCredits | No | {used, limit, remaining} | |
| emailCredits | No | {used, limit, remaining} | |
| billingPeriod | No | Current billing period date range |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description adds value by specifying exactly which resources are checked (API calls, SMS, email, LLM calls), going beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, focused sentence that front-loads the purpose with no redundancy or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and an existing output schema, the description sufficiently explains the tool's purpose. It could mention that it returns current usage and limits, but the output schema likely covers return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, baseline is high, and the description adds meaning by listing what will be returned (usage vs limits for specific resources).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and lists exact resources (API calls, SMS credits, etc.), clearly distinguishing it from sibling billing tools like billing.status or billing.list_plans.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (checking usage vs limits) but provides no explicit guidance on when to use this tool versus alternatives like analytics.dashboard or billing.status.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct resource+action naming (e.g., leads.create, jobs.list), but some overlap exists in analytics tools (dashboard, detailed, financials) and workflow automations (process_lead vs google_ads_pipeline). Descriptions clarify purposes, so slight confusion is possible but limited.
All tools follow a consistent `domain.action` pattern (e.g., leads.create, billing.status). No mixing of camelCase or snake_case. Even complex names like lifecycle.assess or scaling.readiness_score adhere to the convention.
95 tools is far beyond typical well-scoped servers (3-15). While the server aims to cover an entire business management platform, this volume is overwhelming for an agent, making selection and memory difficult.
The tool surface is exceptionally comprehensive, covering formation, hiring, compliance, funding, leads, quotes, jobs, invoicing, payments, marketing, analytics, integrations, webhooks, workflows, and more. Almost no obvious gaps in the lifecycle of running a trade business.