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marcinkuk

ddgs-mcp

by marcinkuk

web_search

Run web searches through multiple engines with automatic fallback, no API key needed. Filter results by region, safety, and time.

Instructions

Web search (web results) via DDGS metasearch. No API key.

Args: query: search query. max_results: number of results (1-25). region: e.g. "us-en", "pl-pl", "de-de", "wt-wt" (worldwide, no region). safesearch: "on" | "moderate" | "off". timelimit: "d" (day), "w" (week), "m" (month), "y" (year), or None. backend: "auto" (randomized multi-engine, recommended) or specific: duckduckgo, bing, brave, google, mojeek, startpage, yahoo, wikipedia, grokipedia. snippet_chars: max snippet length per result (0 = no snippet).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
regionNous-en
backendNoauto
timelimitNo
safesearchNomoderate
max_resultsNo
snippet_charsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The description reveals useful behavioral facts, such as no API key required and use of DDGS metasearch, which are not in annotations. However, with no annotations provided., it does not disclose potential limitations like rate limits or network dependency, leaving some behavioral burden uncovered.

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 front-loaded with the core purpose and API requirement, then uses a clean Args block for parameters. Every line carries useful information and none is redundant with the schema beyond necessary clarification.

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

Completeness5/5

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

Given seven parameters and zero schema descriptions, this descrption covers all of them with concrete options and examples. It also notes key operational context such as no API key and backend choice. With an output schema present, return values need not be described here.

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

Parameters5/5

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

Schema description coverage is 0%, and this descripiton fully compensates. For every parameter it gives allowed values, formats, examples, defaults, or recommendationex: region examples, timelimit semantics, backend options, and max_results range. This is highly actionable for an agent.

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 states a specific verb and resource: web search via DDGS metasearch. It explicitly says 'web results', which distinguishes it from sibling tools like image_search, news_search, and video_search without ambiguity.

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 clear context: this is a web search tool, distinct from other search types. It does not explicitly name alternatives or list when-not-to-use conditions, but 'web results' plus the sibling tool names make the intended use case clear.

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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