export_model

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

With no annotations, the description carries the full burden of behavioral disclosure. It does disclose key behavior: behavior_name 'searches all if omitted' and last_n controls how many recent items are returned, with -1 meaning all. However, it does not mention whether the operation is read-only, what happens for invalid run_ids, or any access requirements. This is adequate but has clear gaps.

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 compact and efficient. The one-line purpose is front-loaded, followed by a concise Args block. Every sentence adds value, and there is no redundant restatement of the tool name or schema. It is appropriately sized for the tool's complexity.

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?

The description covers the core purpose and all parameter meanings, and an output schema exists to define return values, so it does not need to explain those. Given the tool's moderate complexity, the description is largely sufficient. It could be more complete by noting whether the operation is read-only or how results are ordered, but this is not a major gap.

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 fully compensate. It does: each of the three parameters gets a meaningful explanation beyond the schema—run_id identifies the run, behavior_name scopes the search and defaults to all, and last_n controls the number of results with -1 for all. The parameter semantics are complete and unambiguous.

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 opens with a specific verb and resource: 'Locate .onnx model files and checkpoints for a training run.' This clearly states what the tool does and differentiates it from the sibling tools, none of which focus on locating model files. The purpose is immediately understandable and not tautological.

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 gives clear context for when to use the tool: to query a training run and find model files or checkpoints. It explains the role of each argument, including the optional behavior_name and last_n controls. However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of full explicit routing guidance.

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