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matteuccimarco

SLIM MCP Server

slim_fetch_with_options

Fetch web content in SLIM format with configurable inclusion of images and videos. Control response size by excluding media or include them for detailed content.

Instructions

Fetch web content in SLIM format with advanced options.

Same as slim_fetch but with additional control over what content is included.

Use this when you need:

  • To exclude images or videos for faster/smaller responses

  • Specific SLIM levels only

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to fetch
includeImagesNoInclude image descriptions and metadata (default: true)
includeVideosNoInclude video metadata and transcripts (default: true)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the benefit of faster/smaller responses when excluding media, but also claims support for 'Specific SLIM levels only' without any corresponding parameter in the schema. This misleading hint, combined with a lack of detail about errors, return format, or limitations, leaves significant behavioral ambiguity.

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?

The description is reasonably compact, front-loading the core purpose in the first sentence and using a bulleted list for use cases. The 'Same as slim_fetch' sentence is useful for orientation, not redundant. It could be tightened, but each sentence serves a purpose.

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

Completeness3/5

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

The tool has 3 parameters, all well-documented in the schema, but no annotations or output schema. The description provides sufficient context for simple use but introduces an unsupported 'SLIM levels' feature and omits details about response format, error handling, or rate limits. Given these gaps, the description is minimally viable but not thorough.

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?

The input schema has 100% coverage with descriptions for all parameters, so baseline is 3. The description adds marginal value by explaining the performance benefit of excluding images/videos, but it does not clarify the 'SLIM levels' concept or provide extra meaning for the 'url' parameter. The schema already handles the heavy lifting.

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 'Fetch web content in SLIM format with advanced options', using a specific verb and resource. It distinguishes from sibling 'slim_fetch' by noting 'Same as slim_fetch but with additional control over what content is included', making its unique role explicit.

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?

The description provides explicit use cases via a bulleted list: 'To exclude images or videos for faster/smaller responses' and 'Specific SLIM levels only'. It references the sibling tool as the baseline, though it does not explicitly state 'use slim_fetch for basic needs', which would be clearer. Overall, context is clear and actionable.

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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