把采集结果渲染成人能看懂的单文件网页

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

The description thoroughly discloses behavioral traits beyond annotations. It states the tool is not read-only (annotations readOnlyHint=false), mentions the risk of changing target state or occupying shared resources, notes that it produces a one-time snapshot (no auto-refresh), and explains the boundary statement in the page. This adds significant context that annotations alone do not provide.

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 long but well-structured with bullet points and bold headings. It front-loads the core purpose and then details parameters and usage. Every sentence adds value, and the formatting makes it scannable. It's appropriately sized for the tool's complexity, though it could be slightly trimmed without losing essential guidance.

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 tool's return values (counts, badges, next, path), explains error behavior, gives usage examples, and provides risk and boundary notes. It is complete for an agent to invoke it correctly without needing to inspect the schema or other docs.

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?

With schema_description_coverage at 0%, the description compensates by explaining most parameters: data, data_file, view (with options), names, top, out, title/subtitle. It provides concrete formats and defaults (e.g., out default path). However, it does not explain 'max_events' or the exact structure of custom data objects, so it's not fully comprehensive.

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 renders existing collected results into an interactive single-file HTML with specific themes and interactions. It explicitly distinguishes it from other tools by saying it's for visualization, not data capture, and lists accepted data types and output formats. This is a specific verb+resource that differentiates it from siblings like view_guide.

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 provides explicit context on when to use the tool (after data collection) and how to call it with examples for various data types. It gives guidance on handling large data (using data_file to avoid token truncation) and when to use the 'report' view for focused explanations. However, it does not explicitly name alternative tools or say when NOT to use it, though the context is clear enough for an agent to select it appropriately.

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