elenchus_evaluate_edge_cases

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

With no annotations, the description partially handles behavioral disclosure by stating that the tool returns a prompt (not performing evaluation directly). However, it does not discuss authorization needs, side effects, or conditions under which the prompt is generated.

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 no redundancy. The essential information is front-loaded efficiently.

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?

Given the tool's simplicity (1 parameter, no output schema, no nested objects), the description adequately covers what the tool does and what it returns. It could briefly explain 'edge case coverage' or how the prompt is structured, but remains mostly complete for a straightforward 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 coverage is 100% and the description adds no extra meaning beyond what the schema already provides for the single parameter (sessionId). The description does not elaborate on format, constraints, or usage context for the parameter.

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 uses a specific verb (Get) and identifies the resource (LLM evaluation prompt for edge case coverage). It clearly distinguishes from sibling tools like elenchus_submit_llm_evaluation, which likely submits evaluations, while this tool generates a prompt.

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 guidance is provided on when to use this tool versus alternatives such as elenchus_evaluate_convergence or elenchus_evaluate_severity. It does not specify prerequisites, context, or when not to use it.

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