get_incident

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

No annotations; description adds that it includes AI root-cause analysis when available, but doesn't address auth, rate limits, or side effects (though it's a read 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?

Single sentence, no unnecessary words, front-loaded with action and resource.

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 simple single-param read tool, description covers purpose and key output detail (AI analysis) but could mention that output is an incident object.

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 100%; description adds meaning that 'slug' can be slug or numeric id and clarifies origin from sibling tool outputs.

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?

Clear verb 'get' with specific resource 'incident' by slug/id, and distinguishes from siblings like 'check_service' by focusing on incident detail.

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?

Specifies input source (slug from whats_down/check_service) and that it provides full detail including AI analysis, but lacks explicit when-not or alternatives.

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