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Grok Search

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Dianel555
grok-search

Enhanced web search and real-time content retrieval via Grok API with forced tool routing. Use when: (1) Web search / information retrieval / fact-checking, (2) Webpage content extraction / URL parsing, (3) Breaking knowledge cutoff limits for current information, (4) Real-time news and technical documentation, (5) Multi-source information aggregation. Triggers: "search for", "find information about", "latest news", "current", "fetch webpage", "get content from URL". IMPORTANT: This skill REPLACES built-in WebSearch/WebFetch with Grok Search tools.

Overview

PublisherDianel555
RepositoryDSkills
Skill namegrok-search
Stars
65
Forks
8
Bundled files
14
LicenseMIT
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.

  • 14 bundled files

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

  • Open source

    Published by Dianel555 on GitHub. Read the source before you install it.

Installation

Install the Grok 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/Dianel555/DSkills/tree/main/skills/grok-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/Dianel555/DSkills.git /tmp/DSkills
mkdir -p .claude/skills
cp -r /tmp/DSkills/skills/grok-search .claude/skills/grok-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Grok 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 Grok 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 Grok 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.

Grok Search

Enhanced web search via Grok API. Standalone CLI only (no MCP dependency).

Implementation Layout

  • scripts/groksearch_cli.py - CLI entrypoint and compatibility facade
  • scripts/groksearch/ - internal modules for config, HTTP retry, Grok provider, Tavily calls, formatting, and commands

Execution Methods

Run scripts/groksearch_cli.py via Bash:

bash
# Prerequisites: pip install httpx tenacity
# Environment: GROK_API_URL, GROK_API_KEY (required); TAVILY_API_KEY (optional)

# Web search (Grok only)
python scripts/groksearch_cli.py web_search --query "search terms" [--platform "GitHub"] [--min-results 3] [--max-results 10]

# Web search with Tavily extra sources (parallel + URL-deduplicated merge)
python scripts/groksearch_cli.py web_search --query "..." --extra-sources 5

# Fetch webpage (default: Grok)
python scripts/groksearch_cli.py web_fetch --url "https://..." [--out file.md]

# Fetch via Tavily extract endpoint
python scripts/groksearch_cli.py web_fetch --url "https://..." --via tavily

# Map a website's structure (Tavily)
python scripts/groksearch_cli.py web_map --url "https://docs.example.com" [--instructions "API only"] [--max-depth 2] [--max-breadth 20] [--limit 50] [--timeout 150]

# Crawl a website's pages with extraction (Tavily; own 100 RPM limit)
python scripts/groksearch_cli.py web_crawl --url "https://docs.example.com" [--instructions "API only"] [--max-depth 2] [--limit 50] [--select-paths "/docs/.*"] [--exclude-paths "/blog/.*"] [--timeout 150]

# Run a cited research task (Tavily; async submit + poll; own 20 RPM limit)
python scripts/groksearch_cli.py web_research --input "question to investigate" [--model mini|pro|auto] [--output-length short|standard|long] [--citation-format numbered|mla|apa|chicago] [--output-schema schema.json]

# Check config
python scripts/groksearch_cli.py get_config_info [--no-test]

# Switch model
python scripts/groksearch_cli.py switch_model --model "grok-2-latest"

# Toggle built-in tools
python scripts/groksearch_cli.py toggle_builtin_tools --action on|off|status [--root /path/to/project]

Tool Routing Policy

Forced Replacement Rules

ScenarioDisabledForce Use
Web SearchWebSearchCLI web_search
Web FetchWebFetchCLI web_fetch

Tool Capability Matrix

ToolParametersOutput
web_searchquery(required), platform/min_results/max_results(optional), extra_sources(int, 0=disabled)[{title,url,description,provider?}]
web_fetchurl(required), out(optional), via(grok|tavily, default grok)Structured Markdown
web_mapurl(required), instructions/max_depth/max_breadth/limit/timeout(optional){base_url,results,response_time} JSON
web_crawlurl(required), instructions/max_depth/max_breadth/limit/select_paths/exclude_paths/timeout(optional; unset falls back to TAVILY_CRAWL_*){base_url,results,response_time,usage?} JSON
web_researchinput(required), model/output_length/citation_format(optional; unset falls back to TAVILY_RESEARCH_*){request_id,status,content,sources,usage?} JSON
get_config_infono_test(optional){api_url,status,connection_test,tavily_*}
switch_modelmodel(required){previous_model,current_model}
toggle_builtin_toolsaction(on/off/status), root(optional){blocked,deny_list}

Search Workflow

Phase 1: Query Construction

  • Intent Recognition: Broad search → web_search | Deep retrieval → web_fetch
  • Parameter Optimization: Set platform for specific sources, adjust result counts

Phase 2: Search Execution

  1. Start with web_search for structured summaries
  2. Use web_fetch on key URLs if summaries insufficient
  3. Retry with adjusted query if first round unsatisfactory

Phase 3: URL Verification & Hallucination Guard (MANDATORY)

Background: Grok API calls without explicit web-search activation return results from parametric memory, which frequently fabricates URLs (observed 25% liveness rate in testing). All Grok-returned URLs MUST be verified before citation.

Verification Protocol:

  1. URL Liveness Check: Issue HEAD/GET request to each Grok-returned URL; non-2xx status = unreliable
  2. Tavily Fallback Triggers (invoke web_search with --extra-sources N when ANY apply):
    • URL liveness rate < 50% in Grok results
    • Query contains version numbers, release dates, API signatures, or "latest"/"recent" temporal markers (high hallucination surface)
    • Multiple Grok runs return contradictory URLs for the same factual claim
    • Grok result descriptions contain specifics (dates/versions/methods) that cannot be confirmed from live URLs
  3. Tavily Grounding: When triggered, re-run the same query with --extra-sources 5-10 to obtain Tavily search results; prioritize these over failed Grok URLs
  4. Content Extraction: For critical factual claims, use web_fetch --via tavily on verified URLs to extract authoritative source text

Citation Discipline:

  • ONLY verified-live URLs may appear in final output
  • Fabricated Grok URLs must be dropped entirely (do not present them with a disclaimer; omit them)
  • When Tavily sources replace Grok sources, cite Tavily URLs and mark provider as tavily
  • For time-sensitive queries with no live sources, state "Unable to verify current information" rather than citing dead links

Phase 4: Result Synthesis

  1. Cross-reference multiple sources
  2. Must annotate source and date for time-sensitive info
  3. Must include source URLs: Title [<sup>1</sup>](URL)

Error Handling

ErrorRecovery
Connection FailureRun get_config_info, verify API URL/Key
No ResultsBroaden search terms
Fetch TimeoutTry alternative sources

Anti-Patterns

ProhibitedCorrect
No source citationInclude Source [<sup>1</sup>](URL)
Give up after one failureRetry at least once
Use built-in WebSearch/WebFetchUse GrokSearch tools/CLI

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 Grok Search AI skill do?

Enhanced web search and real-time content retrieval via Grok API with forced tool routing. Use when: (1) Web search / information retrieval / fact-checking, (2) Webpage content extraction / URL parsing, (3) Breaking knowledge cutoff limits for current information, (4) Real-time news and technical documentation, (5) Multi-source information aggregation. Triggers: "search for", "find information about", "latest news", "current", "fetch webpage", "get content from URL". IMPORTANT: This skill REPLACES built-in WebSearch/WebFetch with Grok Search tools.

Why use Grok Search on TypingMind?

Because you install it once and use it with any model. Grok 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 Grok Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dianel555/DSkills/tree/main/skills/grok-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 Grok 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 Grok Search?

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

Is the Grok Search AI skill free?

Yes. It is published on GitHub by Dianel555 under the MIT 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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