url_extraction

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

With no annotations, the description carries the full burden and does well: it states the return is compact JSON (not full text), that text mode 'costs less', that HTTP 400+ comes back as a failed read, and that dry_run previews without spending. It omits auth/API-key requirements and any rate limits or latency expectations.

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?

Purpose and primary return shape are front-loaded, and every sentence carries information. The third sentence is long and packs several ideas with em-dashes, making it slightly harder to parse, but nothing is truly redundant.

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?

For a tool with no output schema and no annotations, the description covers return values, mode selection, failure behavior, cost, and dry-run – enough to call it correctly. The missing piece is permission/auth expectations, which the mention of a masked 'key' only hints at.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the schema by explaining the cross-parameter interaction: omit BOTH prompt and schema to get markdown text instead of extracted fields. That behavioral coupling isn't captured in the individual parameter descriptions.

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?

States a specific verb+resource ('Extract structured data from a web page') and enumerates concrete use cases (product listings on Amazon/Shopify/AliExpress, any URL). It clearly distinguishes the tool from siblings like social_research or image_analysis by describing exactly what it extracts and returns.

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?

Explicitly says 'Use when you need specific data, image URLs or the text of a page' and lays out two modes (prompt/schema for structured fields vs. omitting both for cheaper markdown text). It doesn't name when NOT to use it or route to alternative siblings, so it stops short of a full 5.

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