get_model_print_history

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

No annotations are provided, so the description carries the full burden. It discloses important behavioral detail: success-rate metrics cover all materials by default, material scopes them, hash-based lookup may return incomplete history, and identified_by indicates whether the result is shape-precise or file-based. It is a read-only 'get' operation, but side effects and failure modes are not explicitly addressed.

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 longer than average, but it is carefully structured with a clear opening, a prominent best-practice warning, and an organized Args section. Every sentence adds value, though it could be tightened slightly.

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?

Despite the lack of an output schema and annotations, the description is comprehensive: it explains what data is returned, how identifier methods affect results, what identified_by means, and how the material filter behaves. This is sufficient for an agent to invoke the tool correctly with any of the five optional parameters.

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%, but the description fully compensates by explaining every parameter: file_hash, material, model_path, geometric_signature, and geometric_signature_v2. It adds meaningful context such as 'Empty = all materials', 'the best input', and 'if you already have one from fingerprint_model'.

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's function: 'Get all print attempts for a model' and describes the returned history, settings, and quality grades. It distinguishes model_path-based shape identification from hash-based byte identification, but it never explicitly contrasts this with the sibling print_history tool.

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 strong, explicit guidance on when to use model_path versus file_hash, warns that hash-only lookups may miss history, and explains the identified_by response field. However, it doesn't mention when to choose this tool over sibling alternatives like print_history.

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