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convert_multiple_to_markdown

Convert multiple web pages into clean Markdown format for LLM consumption. Specify URLs and optional AI model or instructions.

Instructions

Convert multiple URLs to Markdown using AI via ReviewWeb.site API. Turn multiple web pages into LLM-friendly content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesList of URLs to convert to Markdown
modelNoAI model to use for conversion
instructionsNoOptional custom conversion guidance for the AI
delayAfterLoadNoOptional delay after page load in milliseconds
maxLinksNoMaximum number of URLs to process
debugNoWhether to enable debug mode
api_keyNoYour ReviewWebsite API key
Behavior2/5

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

No annotations are present, so the description carries full burden. It only mentions 'using AI' and 'via ReviewWeb.site API', but does not disclose behavioral traits like rate limits, authorization requirements, or what happens during conversion (e.g., destructive changes).

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?

Description is only two sentences, no redundancy. Front-loaded with the core action. Concise but could be slightly more informative without extra length.

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 7 parameters, no output schema, and no annotations, the description lacks crucial context. It does not explain the output format, the AI model selection, or how the API key is used, making it incomplete for effective use.

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?

Input schema has 100% description coverage for all 7 parameters. The description adds no additional meaning beyond the schema, so it meets the baseline of 3 for high coverage.

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?

Description clearly states 'Convert multiple URLs to Markdown using AI', identifying the verb (convert) and resource (multiple URLs to Markdown). It implicitly distinguishes from sibling 'convert_to_markdown' by specifying 'multiple' and 'multiple web pages'.

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 explicit guidance on when to use this tool versus alternatives. Does not mention the single-URL sibling or provide usage context such as prerequisites or typical scenarios.

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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