extract_json_schema

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

No annotations exist, so the description carries the full burden. It usefully discloses the underlying model (Gemini AI) and the cost (0.030 USDC), which is real behavioral value. However, it says nothing about auth/payment requirements despite an auth_token_or_tx parameter, nor about rate limits or failure behavior.

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?

Front-loaded one-line purpose followed by clearly labeled Usage Guidelines and Returns sections. Every line is relevant; it is tight and scannable with no filler.

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?

An output schema exists, so return-value detail is not required. The description covers purpose, usage context, cost, and return shape, which is sufficient for invocation. The main missing piece is any note on the payment/auth flow implied by auth_token_or_tx.

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 all three parameters are already documented in the schema, making baseline 3 appropriate. The description restates the 'schema_description' concept and the JSON return but adds no syntax or format detail beyond the schema.

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?

Names a specific verb and resource: 'Extracts schema-constrained structured JSON data from any webpage,' and adds distinguishing detail (Gemini AI, 0.030 USDC). It does not explicitly differentiate itself from close siblings like clean_web_content, search_web_quick, or deep_research_topic, but the purpose is unambiguous.

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?

An explicit 'Use when...' condition with concrete examples (pricing, specs, event dates) directly from a URL. It lacks any when-not-to-use guidance or named alternatives among the many sibling web/content tools, so it stops short of the top score.

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