extract_tables

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

The description claims 'Read-only,' but annotations set readOnlyHint: false and destructiveHint: true, a direct contradiction. No other behavioral traits are disclosed, leaving the agent misinformed about side effects.

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?

Two sentences, front-loaded with main action, no redundant phrases. Every word is necessary.

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 tool has no output schema, but the description does not explain what is returned (e.g., JSON rows). Combined with the annotation contradiction, the agent lacks full context. For a simple 2-param tool, it's adequate but not 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% with descriptions. The description adds value by explaining the delimiters detected and that page is optional, but the schema already covers parameter format. Baseline 3, plus one for extra context.

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 table-like structures, specifying pipe, tab, and multi-space delimiters. It stands out from siblings like read_document or convert_to_markdown by focusing on structured tabular data.

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 says 'Use this when you need structured tabular data from a PDF, CSV, or text file,' providing clear context. It does not mention when not to use or list alternatives, but the sibling list helps differentiate.

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