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Web Search

Organization
runxhq
web-search

Discover a bounded set of fresh web source candidates from one explicit search query, preserve provider evidence and reported cost, and prepare source selection for fetching and research.

Overview

Publisherrunxhq
Repositoryrunx
Skill nameweb-search
Stars
105
Forks
109
Bundled files
4
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by runxhq on GitHub. Read the source before you install it.

Installation

Install the Web Search AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/runxhq/runx/tree/main/skills/web-search
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/runxhq/runx.git /tmp/runx
mkdir -p .claude/skills
cp -r /tmp/runx/skills/web-search .claude/skills/web-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Web Search in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Web Search on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Web Search is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Web search

Discover sources for a specific question. The initial search runner uses the selected Exa account for one query and at most 20 results. It normalizes source identity, removes exact duplicate URLs, rejects malformed non-web candidates and preserves the provider operation alongside the result. It does not silently choose another provider, execute extra queries, fetch full pages or write a research conclusion. Exa is the initial executable backend; additional backends need their own declared operations and result mapping.

Search procedure

Choose one concrete information need per query. Include the relevant entity, decision and discriminating terms. Prefer direct evidence: official documentation, first-party announcements, original reports or research. Use domain restrictions when the task requires authoritative sources. Use publication-date bounds for a time-sensitive question, remembering that a publication date is not necessarily the event date. Do not add filters that exclude the contrary evidence you need.

Limit queries and results to the caller's actual budget. Search may consume paid credits. The result includes reported cost when available; missing cost remains unknown. The result cap is not a monetary spending limit. This package adds no billing authority or automatic retry after an uncertain paid request.

Result and composition

search_result contains the query, provider request ID, usable source candidates, discard counts and reported cost. provider_operation retains the exact native provider evidence and account binding. An empty provider result returns no_results; a nonempty response with no usable candidates returns unusable_results. Neither means the question has been researched exhaustively.

Titles, dates and any returned excerpt are discovery metadata, not verified claims or full page content. Fetch selected URLs through web-fetch and feed the actual retrieved packets to research. Check contradictions, source diversity and coverage before drawing conclusions. research over supplied evidence does not perform fresh discovery by itself. Reuse adequate existing evidence rather than repeating a paid search.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Web Search AI skill do?

Discover a bounded set of fresh web source candidates from one explicit search query, preserve provider evidence and reported cost, and prepare source selection for fetching and research.

Why use Web Search on TypingMind?

Because you install it once and use it with any model. Web Search is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Web Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/runxhq/runx/tree/main/skills/web-search. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Web Search?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Web Search?

As many as you like. As long as a model supports skills, you can use Web Search with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Web Search AI skill free?

Yes. It is published on GitHub by runxhq under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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