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Extract FAQ candidates

extract_faqs
Read-only

Pull FAQ question/answer pairs from a business site—checking schema, headings, then question-like text—to seed chatbot demos.

Instructions

Pull FAQ question/answer pairs from a business website: structured FAQ schema first, then question headings, then question-like text lines. Use to seed chatbot demos.

Input Schema

NameRequiredDescriptionDefault
maxNoMax FAQs to return (default 10)
urlYesBusiness page URL (https://...)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds the extraction order (structured FAQ schema, then headings, then text lines), which is useful behavioral context, but does not mention return format, rate limits, or failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with zero waste: it front-loads the core action and extraction strategy, then adds a use case. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with a fully described schema and annotations covering safety. The description states what it does and how it extracts, and implies it returns Q/A pairs. Minor gaps remain regarding return format and behavior when no FAQs are found, but these are small for a simple extraction tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters (url, max) are fully documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, making the baseline 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Pull') and resource ('FAQ question/answer pairs') from a business website, and adds extraction strategy detail. However, it does not distinguish this tool from sibling tools like fetch_page or extract_signals, which prevents a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives one use case ('Use to seed chatbot demos'), which implies usage but does not state when to use this tool versus alternatives or when not to use it. The guidance is implicit rather than explicit.

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