table_extract

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

With no annotations, the description carries the full burden. It does disclose the core behavior (table-to-CSV export) and the output format, but it says nothing about how selector or max_tables affect behavior, potential side effects, or operational constraints. It is adequate but has clear gaps.

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 compact, front-loaded with the primary transformation, and uses a clear WHEN/NOT WHEN structure. Every sentence earns its place, with no redundant 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?

The description is strong for tool selection and usage routing, and there is an output schema to cover return values. However, it fails to explain the selector and max_tables parameters, which are necessary for correct invocation, leaving a notable completeness gap.

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 0%, so the description must compensate. It implies the url parameter by saying 'page', but it does not explain the selector parameter or the meaning of max_tables. An agent cannot confidently set these parameters based on the description alone.

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's function: converting HTML tables from a page into CSV text, with specific examples of use (prices, specs, comparisons). It also distinguishes the tool from siblings by naming extract and fetch_page in the exclusion clause, so an agent can select it correctly.

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 explicit WHEN and NOT WHEN guidance. It says to use this tool when tables are present, and to use extract for arbitrary fields not in tables, or fetch_page when no tables exist. This is direct usage routing with named alternatives.

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