studio_get_view

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

With no annotations, the description carries the full burden. It does disclose what is captured (live canvas plus layer hierarchy) and the return format (image), which is useful, but says nothing about whether the operation mutates state, latency/rate limits, or whether it is safe to call repeatedly. Adequate but thin for an unannotated tool.

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 tight sentences with zero filler; the core action is front-loaded and the return value follows immediately. Nothing could be cut without losing 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?

For a one-parameter capture tool with no output schema, the description tells the agent what comes back (an image) and what it depicts, which is the essential missing piece. It stops short of noting side-effect safety or how scale relates to output fidelity, but no critical invocation detail is absent.

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 coverage is 100% and the single 'scale' parameter is documented in the schema, so the baseline of 3 applies. The description adds no meaning beyond the schema — it never explains how scale affects the capture or the image resolution.

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 gives a specific verb ('captures') and resource ('current live canvas graphic and layer hierarchy'), plus the return type (an image). It is clearly distinguishable from export-oriented siblings like studio_export_file by framing the output as a visual for AI critique, though it never names a sibling explicitly.

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 phrase 'for visual inspection and critique by vision AI models' implies the intended use case (design review / visual QA), but there is no explicit when-to-use vs when-not, and no guidance on choosing this over studio_export_file or design_audit_layout.

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