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

No annotations exist, so the description carries behavioral burden. It discloses key traits: deterministic, no LLM, signed provenance receipt, and pricing. However, it omits failure modes, size limits, or behavior when no tables are found.

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 relatively concise but includes technical jargon (x402, USDC on Base mainnet) that may not be essential for core tool usage. Information is front-loaded with the transformation purpose.

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 three parameters and no output schema, the description explains the basic transformation but lacks details on error handling, limits, or response structure. It provides sufficient context for a straightforward tool but could be more complete.

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 description adds limited value beyond schema. It reiterates index and format options but does not provide deeper meaning or examples.

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 extracts HTML tables from a URL and returns them as typed JSON and CSV. It distinguishes from sibling tools like 'extract', 'fetch', and 'markdown' by focusing specifically on table extraction.

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 provides no guidance on when to use this tool versus alternatives. It mentions cost and determinism but does not explain scenarios where table extraction is appropriate or when siblings would be better.

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