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LareLabs

refinery-mcp

by LareLabs

clean_url

Fetch a public URL and return clean, LLM-ready text with word count. Removes HTML, styles, and scripts to minimize token usage.

Instructions

Fetch a URL with the Refinery Apify actor and return clean LLM-ready text plus word_count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe public URL to clean.
removeStylesNo
removeScriptsNo
Behavior2/5

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

No annotations are provided, so the description must bear the full burden. It omits behavioral traits such as whether fetching is destructive, authentication requirements, rate limits, or error handling (e.g., invalid URL). The mention of 'Refinery Apify actor' is ambiguous.

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

Conciseness3/5

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

The description is concise (one sentence) and front-loaded with the primary action, but it is too brief, sacrificing necessary detail. It could be expanded without becoming verbose.

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

Completeness2/5

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

Given the lack of output schema and low parameter coverage, the description is incomplete. It does not explain the return format, how cleaning is performed, or the role of each parameter. A user cannot fully understand the tool's usage.

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

Parameters2/5

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

Schema description coverage is only 33% (only 'url' has a description). The description adds no meaning for 'removeStyles' and 'removeScripts' parameters, leaving their purpose unclear. It does not compensate for the schema's lack of detail.

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

Purpose5/5

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

The description clearly states the tool fetches a URL via the Refinery Apify actor and returns clean LLM-ready text plus word count. This distinguishes it from siblings like clean_html (likely HTML input) and estimate_savings (cost estimation).

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

Usage Guidelines2/5

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

No usage guidance is provided. The description does not specify when to use this tool versus alternatives like clean_html, nor does it mention prerequisites or scenarios where it should not be used.

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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