observe

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

With no annotations, the description carries the full burden and delivers: it discloses the two labelled surfaces, that background-window text is deliberately excluded and untargetable, that the chrome block prints even when empty (M=0) with a reason, that off-surface text is counted but not listed, and that coordinates are pixels (elements) versus logical points (clicks). This is unusually rich behavioral context.

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?

It is long and dense, but the length is justified given there is no output schema to carry the reply structure. It is front-loaded (purpose, then usage, then surfaces, then reply contents) and uses explicit labels, though a few sentences are packed with multiple clauses that slow scanning.

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?

No output schema exists, so the description must describe the return values, and it does so comprehensively: app name, window, open_windows, known_window, pixel vs point screen size, single_character_scan, off_surface, element format, and the attached PNG. Combined with zero parameters and no annotations, nothing an agent needs to call it correctly is missing.

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?

The tool takes zero parameters, so the baseline is 4 per the rubric. The description spends its detail budget on the reply contract and targeting semantics rather than on parameters, which is the correct allocation here.

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 first sentence gives a precise verb and resource: capture the frontmost window and return a screenshot plus a textual listing of text elements. It also clarifies scope (frontmost window, not all windows) and the two output surfaces, so an agent can distinguish it from execute_plan or focus_app without opening anything else.

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?

Explicit when-to-use guidance: 'Use this once before planning a batch of actions.' It also explains the relationship to downstream calls by defining which surface a step can search and how chrome is reached via target.scope='chrome', including the non-obvious case of a just-opened menu.

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