read_url_for_ai

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

The description adds value by naming the output fields (clean_text, evidence, quality, trace), which annotations do not provide. However, it omits behavioral traits such as the ability to save content (parameters save, save_to) or caching behavior (ttl_seconds, bypass_cache). Annotations already indicate openWorldHint=true, so the description supplements but is incomplete.

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 two sentences are concise and front-loaded, but given the tool's complexity (16 parameters), the description is too brief to be useful. Conciseness is maintained at the cost of essential detail.

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 explains what the tool does and lists output fields, but it fails to cover key contextual aspects: the purpose of the many parameters, save/cache behavior, or when to use it over batch variants. An output schema exists, but the description still leaves significant gaps for a tool with 16 parameters and enums.

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%, and the description provides no information about any of the 16 parameters except implicitly the url. It does not explain the meaning or usage of tags, project, auth_strategy, return_format, fetch_strategy, or any other parameter. This is a severe deficiency.

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: it is a compatibility alias for read_url that reads a single URL, removes UI noise, and returns structured output (clean_text, evidence, quality, trace) for AI agents. The verb 'read' and resource 'URL' are specific, and the mention of returning structured data distinguishes it from simpler inspection tools.

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?

No explicit guidance on when to use this tool vs. siblings like batch_read_urls or inspect_url. It only implies single URL usage but does not state exclusions or alternatives. The phrase 'Compatibility alias for read_url' suggests it is interchangeable with read_url, but no further differentiation is provided.

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