Detect sudden spikes or drops in token usage per organization by comparing recent activity against a rolling baseline to flag anomalies.
Detect usage anomalies: sudden spikes or drops in token usage per org compared to rolling average.
| Name | Required | Description | Default |
|---|---|---|---|
| hours | No | Recent window | |
| baselineHours | No | Baseline window | |
| spikeThreshold | No | Multiple above avg to flag |
Changes observed during successful MCP inspections.
v3.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does disclose the detection method (comparison to a rolling average, flagging spikes and drops), which is genuine context, but says nothing about return format, permissions, or the read-only nature of the operation.
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 tight sentence with the core detection concept front-loaded and no filler. It is appropriately sized, though it could have used a second short sentence for usage routing at no real cost.
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?
There is no output schema and no annotations, and all three parameters are optional, so the description is the only source of behavior. It explains the detection logic adequately but omits what the tool returns (list of anomalies? per-org breakdown?) and any default-behavior guidance.
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 description coverage is 100%, so the schema already documents all three parameters and their bounds. The description's mention of 'rolling average' loosely relates to baselineHours and spikeThreshold but adds no syntax or format detail beyond the schema. Baseline 3 applies.
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?
States a specific verb (Detect) and resource (usage anomalies), and elaborates that the anomalies are sudden spikes or drops in token usage per org measured against a rolling average. This distinguishes it from the sibling openmeter_usage_by_org, which reports raw usage, though it never names that sibling explicitly.
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?
No statement of when to use this tool, when not to, or which sibling to prefer. The purpose implies a monitoring use case, but an agent gets no explicit routing guidance among the many siblings (e.g. openmeter_usage_by_org, suggest_alert_rules).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.