convert_model

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

Without annotations, the description discloses error behavior (raises InvalidKind for unsupported combos) and records lineage (new handle records source_handle). This is good behavioral context, but could mention if the conversion is destructive or non-destructive.

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 extremely concise, with a clear structure including bullet points for supported pairs. No fluff, every sentence provides necessary information.

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?

With an output schema present, the description covers conversion logic, supported pairs, and error handling. It is largely complete, though it could briefly mention the return value type (e.g., new model handle) for clarity.

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?

The input schema has 0% property description coverage, so the description compensates by explaining what source_id is (any model handle) and listing the allowed values for target_kind. This adds meaning beyond the enum 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?

The description clearly states the tool converts a process model from one representation to another, specifies the two parameters (source_id and target_kind), and lists the supported conversion pairs. This differentiates it from sibling tools like discovery or filtering tools.

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 implies usage for converting between model types but does not explicitly state when to use or not use this tool, nor does it mention alternatives. It lacks guidance on prerequisites or contraindications.

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