web_fetch

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

With no annotations, the description carries the full burden, and it does well: it reveals a three-stage fetch strategy (static fetch, Crawl4AI JavaScript rendering, Scrapling stealth fallback) and the Markdown output format. It does not cover failure behavior, but this is a read-only fetch tool and the disclosed behavior is substantive.

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 two tight sentences with no wasted words. The main purpose is front-loaded, and the render guidance earns its place without redundancy.

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 core behavior and render parameter well, but it omits semantics for selector and max_chars, and does not describe failure/error behavior. With no output schema and no annotations, these gaps leave the agent with reasonable but incomplete context.

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?

The schema has 0% description coverage, so the description must compensate. It adds meaning to the render parameter by explaining 'auto' escalation and 'always' for JS-heavy pages, but selector and max_chars are not explained at all, leaving their semantics ambiguous.

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 verb and resource: 'Read one public HTTP(S) URL and return clean LLM-friendly Markdown.' The word 'one' differentiates it from web_crawl, though sibling tools are not explicitly named.

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 gives good guidance on when to use render='always' vs 'auto', but provides no explicit direction on when to choose web_fetch over siblings like web_crawl, web_extract, or web_search. No alternatives or exclusions are mentioned.

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