Web Search

Low Risk

Search the web for information, news, images, and videos using DuckDuckGo's API.

23 stars👍 0 upvotes0

Editorial assessment

Where Web Search fits

Web Search is currently positioned as a research skill for content, growth, and distribution teams shipping repeatable publishing workflows. Based on the available metadata, the core job to be done is straightforward: search the web for information, news, images, and videos using duckduckgo's api.

The current description adds a practical clue about how the skill behaves in the field: a web search skill that retrieves current information, news articles, images, and videos from across the internet. it uses duckduckgo's search api to return clean, formatted results in text, markdown, or json. ideal for research, fact checking, gathering recent information, and collecting web resources. source: https://clawhub.ai/billyutw/web search version: 1.0.0. Combined with a manual install path, this makes Web Search easier to evaluate than pages that only list a name and external link.

Web Search can usually be trialed quickly, as long as the source and permissions still get reviewed. No explicit permission list is published in the current record, so verify the runtime surface in the source repository before rollout.

Best fit

content, growth, and distribution teams shipping repeatable publishing workflows

Install surface

Ask the maintainer for a verified install path before adoption.

Source signal

Public source link available

Workflow tags

Search, Web, and Duckduckgo

Adoption posture

Install command not documented

Risk review

Can usually be trialed quickly, as long as the source and permissions still get reviewed

Best-fit workflows

Web Search is best evaluated in research environments where search the web for information, news, images, and videos using duckduckgo's api

Shortlist it when your team is actively comparing options for search, web, and duckduckgo workflows

Use a disposable workspace for the first pass so you can confirm the install flow, repository quality, and downstream permissions before broader adoption

About

A web search skill that retrieves current information, news articles, images, and videos from across the internet. It uses DuckDuckGo's search API to return clean, formatted results in text, markdown, or JSON. Ideal for research, fact-checking, gathering recent information, and collecting web resources. Source: https://clawhub.ai/billyutw/web-search Version: 1.0.0

Rollout checklist

Review the source repository at https://clawhub.ai/billyutw/web-search and confirm the README, maintenance activity, and install notes are still current.

Document a reproducible install path before trying to operationalize Web Search across multiple machines or contributors.

Capture the permissions and runtime surface during the first install, because the current record does not yet publish a detailed permission map.

Map Web Search against the rest of your stack in search, web, and duckduckgo workflows so the team knows whether it is a standalone tool or a supporting utility.

FAQ

What does Web Search help with?

Web Search is positioned as a research skill. Based on the current summary and tags, it is most relevant for content, growth, and distribution teams shipping repeatable publishing workflows, especially when the workflow requires search the web for information, news, images, and videos using duckduckgo's api.

How should I evaluate Web Search before using it in production?

Start with the source repository or original documentation, document a reproducible install path, and only move to production after you verify permissions, dependencies, and rollback steps.

Why does this page include editorial guidance instead of only the upstream docs?

ClawList is trying to make each skill page more useful than a bare directory listing. That means surfacing practical signals like the install surface, source link, permissions, workflow fit, and rollout considerations in one place.

Who is the best first user for Web Search?

The best first evaluator is usually the operator or engineer already responsible for research workflows, because they can verify whether Web Search matches the current stack, risk tolerance, and maintenance expectations.

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