List Anomalies

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description's role is reduced. It adds domain context (HR/operational/financial anomalies) and mentions filtering capabilities, which is useful beyond annotations. No contradiction.

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?

The description is two bilingual sentences with no wasted words. It front-loads the core purpose and immediately provides usage guidance and filtering options. Every sentence earns its place.

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 list tool with 6 parameters (0 required), output schema present, and clear annotations, the description adequately covers what the tool does, what anomalies it detects, and how to filter. No missing elements given the tool's simplicity.

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%, so baseline is 3. The description groups parameters into type, severity, period, and gives example values for type (e.g., duplicate_clock_in). This adds context but does not provide syntax or formats beyond what the schema already describes.

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 'List HR / operational / financial anomalies detected by the system', specifying the verb (list) and resource (anomalies). It provides concrete anomaly type examples, distinguishing it from sibling tools which deal with other resources.

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 says 'Useful for daily HR review and compliance audits', giving clear usage context. It also mentions filtering by type, severity, or period. While it does not explicitly exclude use cases, the context is sufficient for this unique tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.