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

With no annotations, the description carries the full burden and does well: it discloses account scoping, newest-first ordering, the entry status field, and that 'done' entries carry a GLB download URL valid for 7 days. It does not describe pagination behavior against the limit parameter or what non-'done' entries contain, leaving some 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?

Two sentences, front-loaded with purpose, followed by return-value behavior and then usage guidance. No filler; every clause earns its place.

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?

There is no output schema or annotations, so return-shape disclosure matters, and the description supplies the key facts (entries per task, status, download URL, 7-day validity). It leaves the fuller entry shape (e.g., task_id/model identifiers) implicit, so an agent can still act but with minor uncertainty.

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?

Only one parameter (limit) at 100% schema coverage, so the schema fully documents it (default 20, max 50). The description adds no syntax or semantics beyond the schema, which is the baseline-3 case.

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?

States a specific verb ('Report') and resource (past generate_model tasks) scoped to the calling account, with explicit ordering (newest first). This clearly distinguishes the list operation from the singular get_generation and the create-side generate_model siblings.

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?

Gives an explicit when-to-use: 'Use this to find 3D models generated earlier when the task_id was lost.' That is a concrete trigger. It stops short of naming alternatives (e.g., get_generation for a known task_id) or when-not-to-use, so it falls just short of 5.

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