Returns the calling API key's prepaid balance, monthly limit, current month usage, and a breakdown of how many of each tool the customer can still afford. Free to call.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and idempotent behavior. The description adds valuable context beyond annotations by stating the call is free and by detailing the exact data returned (balance, limit, usage, tool affordability). No contradictions found.
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, well-structured sentence that front-loads the action and lists specific return items without any fluff or repetition. Every word adds value.
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?
For a zero-parameter, no-output-schema tool, the description fully explains what the agent can expect: balance, monthly limit, current usage, and a breakdown of affordable tools. It is sufficient for an agent to decide to call and interpret the result.
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?
The tool takes zero parameters, so the schema covers everything (100% coverage). The description correctly describes what the tool returns, which is the relevant semantic information for a parameterless call.
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 ('Returns') and names exactly what is returned: prepaid balance, monthly limit, current usage, and a tool affordability breakdown. This clearly distinguishes the tool from the sibling security scan and audit tools.
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 implicitly suggests use when checking account balance or affordability, and the 'Free to call' note hints at no cost penalty. However, it does not explicitly state when to use this tool vs. alternatives, or any exclusions.
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 clearly distinct purposes with detailed descriptions that disambiguate overlaps (e.g., dns_security_check vs email_security_audit, ssl_tls_audit vs vet_endpoint). A few compliance lifecycle tools (compliance_framework_check, control_gap_analysis, audit_report_generate) could be confused, but descriptions clarify their sequencing.
All tool names use lowercase snake_case, but the verb/noun order varies (e.g., access_review vs agent_history vs cve_lookup). The pattern is readable and predictable enough, with minor inconsistency in whether the resource or action comes first.
28 tools is on the heavy side, exceeding the 25-tool threshold for 'too many' in the calibration. However, the broad security/compliance domain justifies the count, and each tool covers a distinct aspect, though some consolidation (e.g., email_security_audit vs dns_security_check) could reduce redundancy.
The toolset covers the full security assessment lifecycle: identity/access review, vulnerability discovery and prioritization, compliance frameworks and gap analysis, evidence collection, policy generation, incident triage, and specialized scans (code, secrets, network, web app, MCP/skill supply chain). No obvious critical gaps for the stated purpose.