diagnose_error_screenshot

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It specifies input types (error dialogs, stack traces, logs) and output (localization and fix suggestions), but does not discuss privacy, accuracy limitations, or explicitly state non-mutating behavior beyond the verb '提供建议' implying no side effects. It is adequate but not rich.

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 concise, consisting of three clear sentences. It is front-loaded with the core function, followed by explicit when-to-use and when-not-to-use lists, with no redundant content. Every sentence earns its place.

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 tool has no output schema and no annotations, but the description covers purpose, usage boundaries, and explicitly mentions output as localization and fix suggestions. However, it lacks details on return format, failure handling, or limitations. Given the moderate complexity of diagnosing error screenshots, the description is minimally sufficient but not comprehensive.

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%, meaning all three parameters (image_source, prompt, context) are already fully documented in the input schema. The description adds no extra parameter-level semantics beyond what the schema provides. 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?

The description uses specific verbs like '解析' (parse) and '给出建议' (provide suggestions) targeting error dialogs, stack traces, and log screenshots. This clearly distinguishes it from siblings such as extract_text_from_screenshot (generic text extraction) and analyze_data_visualization (charts), making the tool's purpose unambiguous.

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?

It explicitly states when to use (only when user needs to analyze error messages, locate root causes, or get fix suggestions) and when not to use (do not use for extracting code, UI analysis, or chart interpretation). However, it does not name specific alternative tools, so it falls short of a 5 per the rubric's requirement for alternatives.

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