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

With no annotations, the description carries the full burden and does so thoroughly. It discloses that the model need not be fully translated (viewer polls manifest), that the tool itself requires no APS scopes but the viewer page uses viewables:read/data:read via /token, rate limits, error codes, and that the operation is read-only, pure, and idempotent. This adds rich behavioral context beyond the basic function.

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?

Although longer than typical, the description is highly structured with labeled sections: purpose, when to use, when not to use, scopes, rate limits, errors, side effects. Every sentence adds factual value, and the most important information is front-loaded. No redundancy or filler.

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?

This is a single-parameter, no-output-schema tool, yet the description covers all relevant context: operational behavior (polling manifest), safety profile (read-only, idempotent), constraints (rate limits, errors), and alternatives. It is complete enough for an agent to confidently decide when and how to invoke the tool.

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 100%; the param model_id already has a detailed explanation including format and examples. The description adds a small amount of extra meaning by linking model_id to upload_model and noting idempotence, but this does not significantly improve on the schema's explanation. Baseline 3 is appropriate.

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 'Return a shareable browser URL for the embedded APS viewer and a matching QR code for mobile/XR handoff.' This is a specific verb+resource combination. It also distinguishes itself from siblings by explicitly saying 'Do not use to check translation progress — call get_model_metadata' and 'you need the raw APS URN for programmatic API calls — use the model_id you already have instead.'

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 explicit 'When to use' (hand a stakeholder a URL or print a QR) and 'When NOT to use' (for raw URN or translation progress), naming alternative tools (get_model_metadata). This is exactly the kind of decision guidance the dimension asks for.

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