representation_roundtrip

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

With no annotations, the description carries the full behavioral burden and does so explicitly: 'Read-only' signals safety, and 'Returns the differences as facts only, inferring no semantic verdict' discloses both the output style and the tool's interpretive restraint.

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 dense sentences front-load the most important trait ('Read-only') and then state scope, output behavior, and the sibling routing. No wasted words.

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 two-required-string tool with a simple format enum, the description covers purpose, scope, output nature, and alternative tool. There is no output schema, but the description's 'differences as facts only' plus the format parameter sufficiently sets expectations.

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%, so the schema already describes left, right, and format adequately. The description adds no parameter-level detail, which matches the baseline of 3 for high schema coverage.

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 states a specific verb ('Compare') and resource ('two functions/paths side by side'), and enumerates the comparison dimensions (graph-visible calls, control structure, conversions, side-effect differences). It also differentiates from sibling_compare by specifying this is a deliberate two-sided pairing rather than auto-discovered peers.

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 names the alternative tool and the condition selecting it: 'Use sibling_compare for auto-discovered structural peers, this for a deliberate two-sided pairing.' The encode/decode and serialize/parse examples further clarify when the tool applies.

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