vtable_scan_columns

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 that coordinates are precisely calculated via scenegraph and are directly usable with click_interact without offset, which is valuable behavioral context. However, it does not explicitly state that the tool is read-only or mention any potential performance costs, limitations, or side effects, leaving some transparency 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 moderately concise, with the main purpose front-loaded and the key coordinate usage explained in a few sentences. The bold segments and 'recommended' tag add emphasis without unnecessary verbosity. It is not as tight as a two-sentence description, but each sentence contributes meaningful 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?

The description covers the core behavior, outputs, and integration with click_interact, which is good for a scan tool with an output schema. However, it omits explanation of the input parameters and does not explicitly differentiate from similar sibling tools like vtable_analyze_headers. It is adequate but leaves gaps in parameter understanding and tool selection context.

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%, and the description does not explain the meaning or usage of max_col or iframe_selector. The agent must infer their purpose from parameter names and defaults, which is insufficient. The description entirely fails to compensate for the lack of schema documentation.

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 scans all columns of a VTable (including multi-level headers) and returns specific outputs: column titles, body behavior classification, and header icon viewport coordinates. It uses a specific verb ('scan') and resource ('VTable columns'), and the mention of scenegraph-calculated coordinates strongly differentiates it from generic sibling tools, though it doesn't explicitly name an alternative.

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 explicitly states the use case: '用于规划列头点击（排序/筛选/下拉图标）与列交互' (for planning column header clicks and column interactions). It also explains how to use the returned coordinates with click_interact, providing clear context on when to invoke this tool. It does not mention exclusions or alternatives, but the usage guidance is sufficiently clear.

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