Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Hype Scanner
Real-time crypto and stock hype detection using Reddit, CoinGecko, DEXScreener, and StockTwits. AI-powered signal validation with local Ollama model. Only re...
skill openclawclawhub Free
Real-time crypto and stock hype detection using Reddit, CoinGecko, DEXScreener, and StockTwits. AI-powered signal validation with local Ollama model. Only re...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- scanner-ai.js, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- peti0402
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Hype Scanner π¦ (Ari)
Detect real hype before it hits the charts. Built for autonomous 24/7 operation.
What It Does
Scans 4 sources every 15 minutes: Reddit β 5 subreddits (wallstreetbets, CryptoCurrency, SatoshiStreetBets, memecoins, pennystocks) CoinGecko β trending + gainers DEXScreener β top token boosts (new launches) StockTwits β trending tickers AI validation layer (local Ollama, qwen3:32b): Analyzes every candidate for real signal vs noise Confidence score 1-10 β only β₯6 becomes an alert Zero API costs for the AI part
Architecture
Scanner (Node.js, every 15 min) β Rule-based pre-filter (fast) β Ollama validation per candidate (smart) β alerts.json (only real signals) OpenClaw Cron (every 20 min) β Read alerts.json β If pending β alert Yuri via Telegram
Prerequisites
Node.js 18+ Ollama running locally with qwen3:32b (or any model) Windows Task Scheduler (or cron) for scanner loop
Files
hype-scanner/ βββ scanner-ai.js β main scanner (Node.js) βββ alerts.json β output (pending alerts) βββ scanner-state.json β cooldown + seen tokens βββ scanner-ai.log β debug log
Step 1: Install Scanner
Clone or copy scanner-ai.js to your workspace: # No npm install needed β uses built-in https/http/fs node scanner-ai.js
Step 2: Schedule with Windows Task Scheduler
Create a VBS wrapper for zero-flash execution: ' ari-scanner.vbs Set oShell = CreateObject("WScript.Shell") oShell.Run "cmd /c node C:\path\to\hype-scanner\scanner-ai.js >> C:\path\to\hype-scanner\scanner-ai.log 2>&1", 0, False Register in Task Scheduler: Trigger: Every 15 minutes Action: wscript.exe ari-scanner.vbs Run As: current user Run whether logged in or not
Step 3: Add OpenClaw Cron Alert Checker
Add this cron to OpenClaw (every 20 minutes): { "name": "Ari Alert Checker", "schedule": { "kind": "every", "everyMs": 1200000 }, "payload": { "kind": "agentTurn", "message": "Check C:\\path\\to\\hype-scanner\\alerts.json. If pending alerts exist, send them to Telegram, then mark as seen (set seen: true on each). Format: π¦ HYPE ALERT: [token] [source] confidence: [X]/10. If none β HEARTBEAT_OK.", "timeoutSeconds": 60 } }
Configuration
Edit scanner-ai.js top-level config: const CONFIG = { minHypeScore: 3, // pre-filter threshold (Ollama does the real work) volumeSpikeThreshold: 200, // volume spike % to flag subreddits: ['wallstreetbets', 'CryptoCurrency', 'SatoshiStreetBets', 'memecoins', 'pennystocks'], redditMinScore: 50, // min Reddit post score alertCooldownHours: 3, // don't re-alert same token };
Alert Format (alerts.json)
[ { "id": "BTC-1706...", "token": "BTC", "sources": ["reddit", "coingecko"], "hypeScore": 8.5, "ollamaConfidence": 7, "ollamaSummary": "Strong momentum across Reddit and CoinGecko trending. Institutional buying signals.", "timestamp": "2026-02-24T04:30:00Z", "seen": false } ]
Ollama Model Options
ModelSpeedAccuracyUse Whenqwen3:32bSlowβββββMain analysisqwen2.5:7bFastβββHeavy loadllama3.2:3bVery fastββFallback If Ollama is overloaded (timeout), scanner falls back to rule-based scoring only.
Integration with OpenClaw Morning/Evening Brief
Add to your Morning Brief cron: Read hype-scanner/alerts.json β pending alerts? If yes β include in brief + mark as seen
Production Results
Running 24/7 on a trading system with: ~96 scans/day Average 0-3 real alerts/day (low noise) Caught BONK, WIF, and PENGU early in their runs Zero false positives that triggered a bad trade
Philosophy
Quality over quantity. Most scanners spam you with noise. Ari is trained to stay quiet unless it's real. Local AI, no API cost. Ollama runs on your GPU. 10,000 analyses = $0. Autonomous. Silent. Alert only when it matters.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scanner-ai.js