compare_edge_cases

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

With no annotations, the description carries the full burden. It discloses the expected return format (per-input matrix plus divergences list), default input values, and the meaning of divergence. This is useful behavioral context, though it does not mention resource limits or execution safety.

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 three sentences long, front-loaded with the primary purpose, and uses code formatting for clarity. Every sentence provides necessary detail—defaults, return format, and a prerequisite—without redundancy.

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 presence of an output schema, the description covers all necessary context: purpose, input semantics, defaults, return structure, and a usage prerequisite. It is sufficient for an agent to decide when and how to invoke the 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 description coverage is 0%, so the description must compensate. It explains snippets as a language-to-code mapping and clarifies that inputs are optional with a predefined default set. This adds meaning beyond the raw schema, though it could state explicitly that inputs overrides the default.

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 first sentence, 'Run the same logic in N languages on edge-case inputs and flag divergence,' states a specific verb and resource, clearly distinguishing it from siblings like execute_code or compare_execution. The use of 'edge-case' and 'divergence' pinpoints the tool's unique role.

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 provides an explicit usage hint: 'use translate_code first if you only have one' for preparing inputs. It implies when to use the tool (edge-case testing across languages) but does not contrast with alternative sibling tools like compare_execution, leaving room for more explicit exclusions.

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