extract_structured

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

With no annotations, the description bears full transparency burden. It discloses extraction methods (JSON-LD, OG, etc.), deterministic behavior, and no LLM requirement. However, it omits error behavior (e.g., if no structured data found), rate limits, or authentication needs.

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 a single paragraph that efficiently conveys the tool's purpose and key details. It is front-loaded with the main action. Could benefit from bullet points for readability, but it's acceptable.

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 tool is relatively simple; the description covers core functionality (fetch, extract with schema, sources, deterministic). It mentions output ('returns only the extracted JSON object'). Missing are error handling and edge cases, but overall adequate.

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 100%, so baseline is 3. The description adds no meaningful information beyond the input schema: it essentially repeats the parameter descriptions. No additional syntax or format guidance is provided.

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 fetches a URL and extracts structured data matching a JSON Schema, listing specific fields (title, author, etc.) and sources (JSON-LD, Open Graph). It distinguishes itself from siblings like fetch_extract and fetch_html by specifying it extracts structured data deterministically.

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 clear usage context ('Ideal for articles, products, recipes...') and implies when to use (pages with semantic markup). However, it doesn't explicitly state when not to use or compare to alternative tools like fetch_extract or fetch_html.

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