detect_anomalies

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

Discloses sampling for tables >100k rows (~5%) and dialect-aware sampling, but does not state if the operation is read-only or any side effects. With no annotations, more behavioral details would be beneficial.

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 concise sentences with front-loaded purpose and examples, 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?

Covers core functionality, output type (severity-ranked alerts), and sampling behavior. Lacks detail on output schema or potential limitations, but sufficient for a no-parameter tool.

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?

No parameters defined in schema, so description does not need to add parameter details. Baseline for zero parameters is 4, and description provides adequate context.

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 clearly states the tool scans a table for unusual patterns like volume drops/spikes, data gaps, etc., distinguishing it from sibling tools like analyze_table or data_profile.

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 explicit guidance on when to use this tool vs alternatives, though the context of anomaly detection is clear. Could mention when not to use or compare to related tools.

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