grok-research
Deep research via Grok 4.6 — agentic web + X (Twitter) search.
Skill by crcatala
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/crcatala-grok-research
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: research
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/grok-research
What's inside
- Skill name
grok-research- Description
- Deep research via Grok 4.6 — agentic web + X (Twitter) search. The model autonomously plans searches, browses pages, follows up, and synthesizes comprehensive answers with inline citations. Use for research questions that need synthesized answers, multi-step investigation, real-time info, social sentiment, or travel/comparison planning.
- License
- MIT
- Compatibility
- Requires python3, network access, and XAI_API_KEY.
- Instructions
- 110 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (3)
- SKILL.md
- search.py
- test_search.py
SKILL.md (first lines)
# Grok Research
In the commands below, `{baseDir}` is the directory containing this `SKILL.md`.
Deep agentic research powered by Grok 4.6 via the xAI API. Unlike traditional search APIs that return raw links/snippets, Grok acts as an autonomous researcher — it plans a search strategy, browses pages, makes follow-up queries, cross-references sources, and returns a synthesized answer with inline citations.
**Cost**: depends on token volume and agentic tool calls. Use `--model grok-4.3` for a lower-cost alternative.
## Setup
1. Get an API key at https://console.x.ai/
2. Add to your shell profile:
```bash
export XAI_API_KEY="your-api-key-here"
```
3. Install or upgrade the SDK (the skill requires `xai-sdk` 1.19.0 or newer):
```bash
pip install --upgrade 'xai-sdk>=1.19.0'
```
## Usage
```bash
python3 {baseDir}/search.py "your research query"
```
### Options
| Option | Description |
|--------|-------------|
| `--tools web` | Web search only (no X/Twitter) |
| `--tools x` | X search only (no web) |
| `--tools both` | Both web + X search (default) |
| `--model MODEL` | Model to use (default: `grok-4.6`; use `grok-4.3` for lower cost) |
| `--reasoning-effort low\|medium\|high\|xhigh` | Reasoning effort (default: `high`; `xhigh` requires Grok 4.6 or a newer compatible model) |
| `--no-reasoning` | Deprecated compatibility flag; maps to `--reasoning-effort low` because Grok 4.6 cannot disable reasoning |
| `--max-turns N` | Optional agentic-search cap (fewer turns = faster/cheaper); omit it for the provider default |
| `--profile general\|factual\|comparison\|news\|social\|literature` | Research policy; `general` verifies the premise and is the sensible default for most tasks |
| `--format prose\|claims` | Output normal prose or a strict claims-and-evidence JSON object |
| `--system "prompt"` | Additional system guidance appended to the selected profile |
| `--verbose` | Show tool calls on stderr; reasoning totals remain in the footer |
| `--json` | Output structured JSON (content, citations, usage, tool_calls) |
### Examples
```bash
# Deep research question
python3 {baseDir}/search.py "What are the latest developments in WebAssembly?"
# Web-only (skip X/Twitter)
python3 {baseDir}/search.py "Python 3.13 new features" --tools web
# Social sentiment (X/Twitter focused)
python3 {baseDir}/search.py "What are developers saying about Bun runtime?" --tools x
# Travel planning
python3 {baseDir}/search.py "10-day Japan trip April 2026, cherry blossoms, budget tips" --tools web
# Comparison research
python3 {baseDir}/search.py "Compare Zed vs Cursor vs VS Code for AI coding 2026"
# Current events / news
python3 {baseDir}/search.py "biggest news stories this week"
# Use a comparison policy (the default general policy fits most research tasks)
python3 {baseDir}/search.py "best terminal emulators 2026" --profile comparison --system "Focus on Linux."
# Emit auditable claims with source-by-source supporting evidence
python3 {baseDir}/search.py "Is Deno 3 released?" --profile factual --format claims
# Quick, bounded factual lookup
python3 {baseDir}/search.py "who won the Super Bowl?" --model grok-4.3 --max-turns 2
# Lower reasoning effort for faster/cheaper research
python3 {baseDir}/search.py "summarize latest AI model releases" --reasoning-effort low --max-turns 2
# Structured JSON output (for piping/processing)
python3 {baseDir}/search.py "Anthropic Claude latest updates" --json
```
### Output
The default `general` profile first verifies the premise of the request. It reports unsupported or negative findings with search scope and uncertainty rather than treating missing results as proof of nonexistence.
**Turn guidance:** omit `--max-turns` for normal, comparative, or claims-and-evidence research—the provider can use the depth it needs. Use `2-3` only for a simple, known-answer lookup. For premise verification or `--format claims`, use at least `6` if you need a cap; `8-12` is safer for comparisons or disputed/negative findings.
The default prose format streams a synthesized answer with `[[1]](url)` style inline citations, followed by metadata. `--format claims` returns a JSON object with precise claims, confidence, source-by-source support, and limitations. The CLI rejects malformed claims output, including empty claims arrays, missing evidence, invalid confidence/source types, empty fields, and non-HTTP(S) source URLs.
```
[Synthesized answer with inline citations...]
---
Model: grok-4.6 | Reasoning effort: high | Time: 42.3s
Tokens — prompt: 17000, completion: 1800, reasoning: 1500, cached: 9000
Tools used: {'SERVER_SIDE_TOOL_WEB_SEARCH': 8, 'SERVER_SIDE_TOOL_X_SEARCH': 2}
Citations (45):
https://example.com/source1
...
```
### Pricing
- **Grok 4.6 tokens**: $2.00/1M input, $0.50/1M cached input, $6.00/1M output
- **Grok 4.3 tokens**: $1.25/1M input, $0.20/1M cached input, $2.50/1M output
- **Web Search**: $0.005 per tool call
- **X Search**: $0.005 per tool call
See [xAI's pricing page](https://docs.x.ai/developers/pricing) for current rates.From crcatala/skills, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 1, 2026 (28 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/crcatala/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
grok-research skill. Agent Mart. https://agentmart.dev/skills/crcatala-grok-research (last updated 2026-10-24)