Check API token usage per bot per day. Shows which bots are consuming the most tokens and flags anomalies. Use this to monitor costs and catch runaway knowledge files.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Number of days to show (default: 3) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent behavior. Description adds that it flags anomalies, providing additional behavioral context beyond annotations.
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?
Two sentences efficiently cover purpose, output, and usage motivation with no redundant information.
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?
With one parameter, no output schema, and strong annotations, the description fully covers the tool's behavior and use case, leaving no gaps.
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?
Schema coverage is 100% with a clear description for the 'days' parameter. The main description adds no further parameter details beyond what the schema provides, meeting baseline.
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?
Description uses specific verb 'Check' and resource 'API token usage per bot per day,' clearly distinguishing from sibling tools like accountability_check or page_health which focus on other aspects.
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?
States purpose ('monitor costs, catch runaway knowledge files') and gives clear context, but does not mention when not to use or provide explicit alternatives.
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, but there is some overlap among multiple audit/check tools (e.g., accountability_check, drift_audit, security_audit). However, descriptions and naming help differentiate their specific scopes, so ambiguity is low.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., check_archive_safety, propagate_family_member), making them predictable and easy to understand.
33 tools is on the high side, but the server covers a broad domain (system health, audits, propagation, session management, etc.). The count is justified by the comprehensive scope, though it may feel heavy for agents.
The tool set covers the entire lifecycle of system management: health monitoring, audits, propagation, sessions, compliance, and more. No obvious gaps for the stated purpose of a nervous system framework.
