extract_pricing_table

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

With no annotations, the description carries the full behavioral burden. It discloses the extraction output categories, but not whether supplying url triggers a network fetch, whether both parameters are optional (schema says 0 required, defaults ''), what happens if both are empty, whether ant/Javascript-rendered pricing pages work, or any rate/timeout limits.

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?

Front-loaded with a compact capability summary followed by a short Args list; every line carries information. The 'Zero-Selector SaaS & Product Pricing Table Extractor:' label is slightly marketing-flavored but still communicates a real differentiator, so it earns its place.

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?

An output schema exists, so return values need not be spelled out, and the description even previews the extracted fields. However, for a tool with two ambiguous optional inputs and no annotations, it should clarify input interaction, fetch behavior, and failure conditions to be fully self-sufficient.

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, and it partially does: url is defined as the pricing page to scrape, and html_text as raw HTML or text 'of the pricing section', which usefully narrows the expected scope of that input. It does not explain precedence when both are supplied or that at least one is effectively required.

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 states a concrete verb and resource ('extract pricing table') and enumerates exactly what is returned: tier names, price amounts with currency variants, billing cycles, feature bullets, popular badges, and CTA links. That level of specificity separates it cleanly from generic siblings like scrape_url and extract_structured, which carry no domain knowledge about pricing pages.

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?

Usage is only implied: 'pricing page URL to scrape and analyze' plus 'Zero-Selector' hints this is the purpose-built path for pricing pages rather than raw scraping. There is no explicit when-to-use vs. scrape_url/extract_structured, no guidance on choosing between the url and html_text inputs, and no stated exclusions.

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