Get normalized AWS Cost Anomaly Detection anomalies for a date range. The adapter drains NextPageToken internally.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| account | No | ||
| end_date | No | ||
| days_back | No | ||
| start_date | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a safe read operation. The description adds that the adapter drains NextPageToken internally, which is a valuable behavioral detail about pagination not captured in 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: the first clearly states the action, the second adds a pagination note. No 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?
The description covers the core function and pagination, and annotations handle safety, but it lacks parameter details and return information. Given the simple tool, it is fairly complete.
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 0%, and the description only hints at date range via 'for a date range,' not explaining limit, account, or specific date formats. It does not compensate for the lack of schema descriptions.
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 clearly states 'Get normalized AWS Cost Anomaly Detection anomalies' with a specific verb and resource, and the date range scope distinguishes it from cost and forecast siblings.
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 for anomaly detection but does not explicitly compare with siblings or provide when/when-not guidance. The date range mention gives some context but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.