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CutGPT Research & Fact-Check

Inspect a website's background

inspect_source
Read-onlyIdempotent

Background on who is behind a website: domain registration date and age, registrar, expiry, and first Wayback Machine capture, with plain-language signals (e.g. 'Domain was registered 12 days ago').

Use it to vet unfamiliar sources before trusting or citing them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAny URL or domain from the site you want to vet.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

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, openWorldHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is fully covered structurally. The description adds the nature of the output ('plain-language signals') but says nothing about latency, caching, or failure modes when a domain is unregistered or absent from Wayback.

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

Conciseness4/5

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

Two sentences, front-loaded with the data inventory and closed with the use case; nothing is padding. The field list partially restates what the output schema already exposes, which keeps it just short of a 5.

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?

With one fully documented parameter, rich annotations, and an output schema, the description only needs to supply purpose and usage, both of which it does. It is nearly complete, with only the absence of failure/edge-case behavior leaving a small gap.

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?

There is a single parameter at 100% schema description coverage ('Any URL or domain from the site you want to vet'), so the schema already carries the semantics. The description confirms the website-vetting scope but adds no format or edge-case detail (e.g. bare domain vs full URL), so baseline 3 is right.

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 names a specific verb-plus-resource ('Background on who is behind a website') and enumerates the exact data returned: domain registration date and age, registrar, expiry, first Wayback capture. That enumeration implicitly separates it from siblings like read_url (content) and find_archived_page (snapshots), though it never names an alternative explicitly.

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

Usage Guidelines4/5

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

'Use it to vet unfamiliar sources before trusting or citing them' gives a clear triggering context for the tool. There are no exclusions or named alternatives, so it stops short of the when-not/alternative guidance that a 5 requires.

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

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