detect_cascading_alerts

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

Annotations already declare readOnly, idempotent, non-destructive. Description adds that it infers directional dependencies and returns root cause candidates, providing context beyond annotations. No contradictions.

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?

Concise: uses bullet points and examples without fluff. Front-loaded with purpose and use cases. Each sentence adds value.

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?

Output schema exists, annotations cover safety. However, missing parameter descriptions for instance/instances and no guidance on default behavior when both are null. Adequate but not fully comprehensive for a moderately complex 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?

Schema covers only 33% (temporal_window has description). Description does not explain 'instance' or 'instances' parameters. No additional parameter guidance beyond schema.

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?

Clearly states the tool detects cascading alert patterns with directional dependency inference. Differentiates from sibling tools like alertmanager_list_alerts by focusing on propagation patterns. Examples illustrate typical use cases.

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?

Explicitly lists use cases (trace propagation paths, identify root causes, understand dependencies) and provides example queries. Lacks explicit instructions on when NOT to use this tool, but scenarios are well defined.

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