Borrowing it
Nothing to install: this file belongs to mzkrasner/grok-x-insights-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mzkrasner/grok-x-insights-mcp/main/.claude/skills/grok-insights/SKILL.mdgit clone --depth 1 https://github.com/mzkrasner/grok-x-insights-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mzkrasner/grok-x-insights-mcp/grok-insights)<a href="https://agentmods.dev/skills/mzkrasner/grok-x-insights-mcp/grok-insights"><img src="https://agentmods.dev/badge/skills/mzkrasner/grok-x-insights-mcp/grok-insights/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mzkrasner/grok-x-insights-mcp/grok-insights"><img src="https://agentmods.dev/badge/skills/mzkrasner/grok-x-insights-mcp/grok-insights.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.01032 |
| Opus 5 | $0.00015 | $0.00516 |
| Sonnet 5 | $0.00006 | $0.00206 |
| Haiku 4.5 | $0.00003 | $0.00103 |
Grade A, and why
grok-insights scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grok X Insights (Local CLI)
Get real-time social intelligence from X/Twitter using the locally installed Grok CLI. This skill uses the CLI built from this repository.
Arguments
$ARGUMENTS
- A search query or topic to analyze (e.g., "artificial intelligence", "climate change")
- If blank, will prompt for a topic
Prerequisites
The CLI is installed globally when you run npm install in this repo. Verify it's available:
grok --version
Ensure GROK_API_KEY is set in your environment or .env file.
Available Commands
1. Search Posts
Analyze X/Twitter posts about a topic with sentiment and themes.
grok search "QUERY" --time-window 4hr --limit 30 --analysis both -f text
Options:
--time-windowor-t: 15min, 1hr, 4hr, 24hr, 7d (default: 4hr)--limitor-l: Max posts to analyze, 1-50 (default: 50)--analysisor-a: sentiment, themes, both (default: both)-for--format: Output format, json or text (default: json)
2. Analyze Topic
Deep analysis with custom aspects.
grok analyze "TOPIC" --aspects "sentiment,influencers,controversy" --time-window 24hr -f text
Options:
--aspectsor-a: Comma-separated aspects to analyze--time-windowor-t: Time window for analysis--limitor-l: Max posts to analyze
3. Get Trends
Identify trending topics and discussions.
grok trends --category technology --limit 30 -f text
Options:
--categoryor-c: technology, politics, sports, entertainment--limitor-l: Max posts to analyze for trends
4. Chat with Grok
General chat, optionally grounded in X/Twitter data.
grok chat "What are people saying about AI?" --search -f text
Options:
--searchor-s: Enable X/Twitter search--search-limitor-l: Max posts to search if search enabled--temperature: Response creativity 0.0-1.0 (default: 0.7)
Process
Step 1: Understand the request
Determine what kind of analysis the user wants:
- Search: Specific topic analysis with sentiment/themes
- Analyze: Deep dive with custom aspects
- Trends: What's trending right now
- Chat: General question, optionally with X data
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 159 lines · 30 tokens per session scan A ce0028765946
grok-insights is a skill published in the GitHub repository mzkrasner/grok-x-insights-mcp (3 stars, last pushed 6mo ago), licensed MIT. It adds 30 tokens to every session and 1,032 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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