inspect_url

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds value by explaining that the tool returns diagnostic data (fetch, extraction, quality, trace) without returning the full text. This clarifies the behavior beyond the annotations. However, it does not mention caching behavior or auth requirements, which are partially covered by parameters.

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 extremely concise: two sentences with no filler. It front-loads the core action ('Diagnose why a public URL reads poorly') and immediately specifies the output. Every word contributes to understanding.

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?

Given the tool has 5 parameters (including enums) and an output schema, the description covers the high-level purpose but lacks details on parameter semantics and how to interpret diagnostics. While the output schema might fill some gaps, the description should provide more context for proper usage, especially for a diagnostic tool.

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%, meaning the description does not explain any of the 5 parameters (url, bypass_cache, auth_strategy, fetch_strategy, html_preview_chars). The agent must rely solely on parameter names and types, which may be insufficient for correct invocation. The description should have provided guidance on parameter usage.

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's purpose: 'Diagnose why a public URL reads poorly.' It specifies the output (fetch, extraction, quality, and trace diagnostics) and what it does not return (full clean_text), distinguishing it from sibling tools like read_url that likely return full text.

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 indicates when to use the tool (to diagnose reading quality issues) but does not provide explicit guidance on when not to use it or how it compares to alternatives among the sibling tools. The context is implied but not fully clarified.

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