research_pack

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

With no annotations provided, the description carries the burden of behavioral disclosure. It reveals the paid nature, the x402 payment requirement, and the retry behavior with normalized results. However, it does not mention error handling or what happens after payment failure, which would be helpful.

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 concise with three sentences, each contributing distinct value: purpose, usage guidance, and payment behavior. It is front-loaded and contains no redundant information.

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?

Given the tool's complexity (5 parameters, payment workflow) and the existence of an output schema, the description covers the main workflow and payment mechanism adequately. It could elaborate on parameter interactions (e.g., how max_results and extract_pages relate) but is sufficient for an agent to understand the tool's role.

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 parameters are already well-described. The description adds overall context about the workflow (search, extraction, JSON, citations) but does not provide additional details for individual parameters beyond what the schema offers. Baseline 3 is appropriate.

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 runs a full paid research workflow combining search, extraction, JSON, and citations. It distinguishes itself from raw search results and sibling tools like extract_page and search by emphasizing it produces a compact source-backed packet.

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 explicitly advises using this tool when an agent needs a compact research packet rather than raw search results. It also clarifies payment behavior: unpaid calls return x402 terms, paid retries return normalized results. This provides clear context and differentiation.

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