get_table

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 explains key behaviors: uses the first matching element's first <tr> as headers, defaults to the first table, and adds a `<header>_href` key for cells containing links. It does not mention error handling for absent tables, but the disclosed parsing rules are sufficient for a read-only operation.

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 tightly written, front-loading the core purpose in the first sentence. Additional details about selector behavior and usage guidance are relevant and concise, with no obvious filler or repetition.

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?

For a tool with one optional parameter and no annotations, the description covers the essential invocation details: input selection, default behavior, output format, and extra href key. It stops short of explaining edge cases like missing tables or multi-table ambiguity, but given the low complexity, it is reasonably 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 description coverage is 0%, but the description fully explains the only parameter, `selector`: it picks which table, defaults to the first <table>, and gives a concrete example ('table#programsGrid'). This adds substantial meaning beyond the raw schema definition.

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 opens with a specific verb and resource: 'Parse an HTML table on the current page into rows of {column_header: cell_text}'. It clearly distinguishes itself from siblings by explicitly naming get_page_content as the alternative for non-tabular data, and by noting that results can be passed directly to add_record.

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 states when to use this tool: 'Use this instead of eyeballing get_page_content for tabular data'. It provides an alternative tool and gives downstream workflow guidance ('pass the results straight to add_record'), making the intended usage context unambiguous.

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