desktop_perceive

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

With no annotations, the description carries the full burden and does substantial work: it discloses the two-channel process, the per-window consistency verdict, the enumerated failure reasons (minimized / offscreen / blank), and a non-obvious side effect — results are auto-written into the memory layer. It does not mention cost/latency of per-window visual sampling or that image data is returned, which is why it is not a 5.

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?

Four short lines, front-loaded with the core capability and followed by mechanism, output and follow-up. No filler, though the parenthetical '(核心能力)' is a self-assessment that adds little for an agent.

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, and the description compensates by stating what is returned (per-window consistency verdict plus inconsistency reasons). It leaves a gap about the image payload implied by format/maxWidth/includePng, but for a zero-required-parameter perception tool the essentials are covered.

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%, so format, maxWidth and includePng are already fully documented in the schema. The description adds no parameter-level meaning beyond the visual-sampling concept, so the baseline 3 applies.

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 mechanism (dual-channel: structural window enumeration + visual region sampling with cross-validation) and the resource it operates on (each desktop window). This is clearly distinct from a plain capture tool like desktop_screenshot or desktop_list_windows, though it never names those siblings explicitly to make the contrast airtight.

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 establishes the follow-up flow ('结果会自动写入记忆层，之后可用 memory_recall 按指代定位'), which is useful routing guidance. But it never says when to prefer this over desktop_screenshot or desktop_list_windows, nor any precondition or exclusion — the when-to-use is only inferable from '核心能力'.

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