| name | daily-alpha-scanner |
| description | One-click daily alpha scanner that runs a full 8-step on-chain research pipeline using OKX OnchainOS + social sentiment + historical backtesting + trend monitoring & alerts: (1) Hot Token Discovery with narrative categorization, (2) Smart Money / KOL / Whale buy-signal tracking, (3) Social Sentiment Scan via crypto news (opennews), Reddit, and Twitter KOL tracking (xreach), (4) Meme Coin launchpad scanning with dev reputation and bundle/sniper detection, (5) Batch security audit (honeypot, mintable, fake LP, wash trading), (6) Historical Signal Validation via DexPaprika OHLCV — backtest what happened after past smart money entries, (7) Trend Monitoring & Alerts via TrendRadar (Chinese platforms: Zhihu/Weibo/Bilibili) + Google Trends (global search interest) — detect tokens trending BEFORE they pump, plus multi-channel alert push (Telegram/Feishu/Slack/DingTalk/WeChat), (8) Consolidated briefing with 8-dimension composite scoring (0-100) and BUY / WATCH / AVOID verdicts. Supports Solana, Base, Ethereum, BSC, Arbitrum. Use when the user wants a daily market scan, alpha discovery, token recommendations, or asks 'what to buy today'. Trigger keywords: daily scan, alpha scanner, today's alpha, what to buy, market scan, daily briefing, 每日扫描, 今日推荐, 扫链, 今天买什么, 市场扫描, 链上日报, 每日研报, 趋势预警. |
| license | MIT |
| compatibility | Requires onchainos CLI v3.1+ and OKX Web3 API key (OKX_API_KEY, OKX_SECRET_KEY, OKX_PASSPHRASE). Internet access required for on-chain data queries. |
| metadata | {"author":"zhuyansen","version":"4.0.0","homepage":"https://github.com/zhuyansen/daily-alpha-scanner"} |
Daily Alpha Scanner
A systematic 8-step pipeline that scans on-chain data + social sentiment + historical backtesting + trend monitoring & alerts across multiple chains and produces a consolidated briefing with purchase recommendations.
Pipeline
Step 1: Hot Tokens → Step 2: Smart Money → Step 3: Social Sentiment
↓ ↓ ↓
Step 4: Meme Scan → Step 5: Security Audit (batch scan all candidates)
↓
Step 6: Signal Backtesting (DexPaprika OHLCV — historical validation)
↓
Step 7: Trend Monitoring & Alerts (TrendRadar Chinese platforms + Google Trends global)
↓
Step 8: Consolidated Briefing + Purchase Recommendations (8D scoring)
Prerequisites
Required: OKX OnchainOS
which onchainos && onchainos --version
If missing: curl -sSL https://raw.githubusercontent.com/okx/onchainos-skills/main/install.sh | sh
Required env vars: OKX_API_KEY, OKX_SECRET_KEY, OKX_PASSPHRASE (Web3 API key from https://web3.okx.com/onchainos/dev-portal)
Social Sentiment Tools (graceful degradation — all optional, use what's available)
Check availability in order of priority:
curl -s "https://www.reddit.com/r/cryptocurrency/hot.json?limit=1" -H "User-Agent: agent-reach/1.0" | python3 -c "import json,sys; print('Reddit: OK')" 2>/dev/null || echo "Reddit: unavailable"
which xreach && xreach search "test" --json -n 1 --proxy http://127.0.0.1:7890 2>/dev/null && echo "xreach: OK" || echo "xreach: unavailable"
At least one social source must work. If all fail, Step 3 is skipped and social score defaults to 50 (neutral).
Historical Data: DexPaprika (free, no API key)
curl -s "https://api.dexpaprika.com/search?query=TROLL" | python3 -c "import json,sys; print(json.loads(sys.stdin.read()).get('tokens',[])[0])"
If DexPaprika API is unreachable, Step 6 is skipped and backtestScore defaults to 50 (neutral).
Trend Monitoring: TrendRadar + Google Trends (graceful degradation — both optional)
If TrendRadar is unavailable, Chinese platform trend data is skipped. If Google Trends is unavailable, global trend data is skipped. If both are down, Step 7 is skipped and trendScore defaults to 50 (neutral).
Execution
User Parameters
Ask the user before starting (or use defaults):
| Parameter | Default | Options |
|---|
| Chains | Solana + Base | Solana (501), Ethereum (1), Base (8453), BSC (56), Arbitrum (42161) |
| Focus | All narratives | AI, Meme, DeFi, Infra, BTC-eco, Political |
| Risk tolerance | Medium | Conservative, Medium, Aggressive |
| Output | Terminal | Terminal, Markdown file |
If the user just says "扫一下" or "daily scan" without parameters, use defaults (Solana + Base, all narratives, medium risk).
Step 1: Hot Token Discovery
Goal: Find trending tokens across target chains, categorize by narrative.
1.1 Fetch Trending Tokens
Run in parallel for each target chain:
onchainos token hot-tokens --chain <chainId> --limit 20
onchainos token trending --chains <chainIds> --sort-by 5 --time-frame 4 --limit 30
1.2 Extract & Categorize
From the results, extract for each token:
tokenSymbol, tokenContractAddress, chainIndexprice, change (24h %), volume, marketCap, liquidityholders, top10HoldPercent, bundleHoldPercent, devHoldPercentriskLevelControl (1=low, 2=medium, 3=high)
Categorize by narrative based on token name, symbol, and tags:
- AI/Agent: tokens related to AI, agents, virtual, autonomous
- Meme: animal names, cultural references, ironic/funny names
- DeFi: DEX tokens, lending, yield, staking
- Infra: L1/L2, bridges, oracles, tooling
- BTC-eco: BTC wrappers, ordinals, BTC-related
- Political: political figures, events
- Stablecoin/Yield: USD-pegged, yield-bearing stablecoins
1.3 Filter Criteria
Remove tokens that are obvious noise:
- Top10 concentration > 80% (extreme whale control)
- Market cap < $5K (dust)
- Volume/MCap ratio > 100x (likely bot wash trading)
- Zero holders or zero liquidity
Keep a shortlist of top 15-20 interesting tokens for further analysis.
Step 2: Smart Money Signal Scan
Goal: Identify what smart money, KOLs, and whales are actively buying.
2.1 Aggregated Buy Signals
Run in parallel for each target chain:
onchainos signal list --chain <chainId> --wallet-type 1 --limit 10
onchainos signal list --chain <chainId> --wallet-type 2 --limit 10
onchainos signal list --chain <chainId> --wallet-type 3 --limit 10
2.2 Extract Signal Data
For each signal entry:
token.symbol, token.tokenAddress, token.marketCapUsdtriggerWalletCount (number of smart money addresses buying)amountUsd (total buy amount)soldRatioPercent (how much they've already sold — key metric!)token.top10HolderPercent, token.holders
2.3 Signal Quality Scoring
Rate each signal:
- Strong: 5+ wallets buying, soldRatio < 30%, marketCap > $100K
- Medium: 3+ wallets buying, soldRatio < 60%
- Weak: 1-2 wallets, soldRatio > 70% (already exiting)
- Exit signal: soldRatio > 90% (smart money dumping)
2.4 Cross-reference with Hot Tokens
Flag tokens that appear in BOTH Step 1 (trending) AND Step 2 (smart money buying) — these have the strongest alpha signal.
Step 3: Social Sentiment Scan
Goal: Gauge market sentiment from crypto news, Reddit communities, and Twitter/X KOL discussions for candidate tokens from Steps 1-2.
3.1 Determine Available Sources
At the start of this step, check which social tools are available:
Source priority (use all that work):
1. opennews MCP → mcp__opennews__search_news_by_coin (if MCP configured)
2. Reddit API → curl to reddit JSON endpoints (always available)
3. xreach CLI → Twitter search (if installed + authenticated)
4. opentwitter → Twitter MCP (if MCP configured)
Record which sources are active. If none work, skip this step entirely and assign socialScore = 50 (neutral) for all tokens.
3.2 Crypto News Sentiment (opennews)
For each candidate token (top 10 from Steps 1-2 combined):
Tool: mcp__opennews__search_news_by_coin
Args: coin = "<TOKEN_SYMBOL>", limit = 5
From results, extract:
- newsCount: how many articles in the last 24-48h
- sentiment: classify each headline as bullish / bearish / neutral
- catalysts: any major events (listing, partnership, hack, regulation)
Scoring:
- 5+ bullish articles, no bearish →
newsSentiment = 90
- 3+ bullish, no bearish →
newsSentiment = 75
- Mixed (both bullish & bearish) →
newsSentiment = 50
- Mostly bearish →
newsSentiment = 25
- No news at all →
newsSentiment = 50 (neutral, not penalized)
3.3 Reddit Community Buzz
For each candidate token, search crypto subreddits:
curl -s "https://www.reddit.com/r/cryptocurrency+CryptoMoonShots+solana+defi/search.json?q=<TOKEN_SYMBOL>&limit=10&sort=new&t=week" \
-H "User-Agent: daily-alpha-scanner/2.0"
From results, extract:
- postCount: number of posts mentioning this token in the past week
- totalScore: sum of upvotes across all matching posts
- commentCount: total comments (engagement depth)
- sentimentRatio: ratio of positive vs negative posts (read titles + top comments)
Scoring:
- 10+ posts, totalScore > 100, mostly positive →
redditBuzz = 85
- 5+ posts, totalScore > 30, mixed-positive →
redditBuzz = 65
- 1-4 posts, low engagement →
redditBuzz = 45
- Zero mentions →
redditBuzz = 30 (no buzz is slightly bearish for a "hot" token)
3.4 Twitter/X KOL Tracking (if available)
If xreach CLI is available:
xreach search "$TOKEN_SYMBOL crypto" --json -n 15 --proxy http://127.0.0.1:7890
If opentwitter MCP is available, use its search tool instead.
From results, extract:
- tweetCount: number of tweets in past 24-48h
- kol_mentions: tweets from accounts with 10K+ followers
- sentiment: bullish / bearish / neutral ratio
- engagementRate: avg (likes + retweets + replies) per tweet
Scoring:
- 3+ KOL mentions, mostly bullish, high engagement →
twitterScore = 90
- 1-2 KOL mentions, positive sentiment →
twitterScore = 70
- Mentions exist but mixed/low engagement →
twitterScore = 50
- No data (tool unavailable) →
twitterScore = null (excluded from average)
3.5 Social Score Calculation
Combine available sources into a single socialScore (0-100):
If all 3 sources available:
socialScore = newsSentiment × 0.40 + redditBuzz × 0.30 + twitterScore × 0.30
If 2 sources available:
socialScore = weighted average of available sources (equal weights)
If 1 source available:
socialScore = that source's score
If 0 sources:
socialScore = 50 (neutral)
3.6 Social Signal Flags
Flag notable patterns:
- 🔥 VIRAL: socialScore > 80 — strong positive buzz across multiple platforms
- 📰 NEWS_CATALYST: major news event detected (listing, partnership, whale buy)
- 🤫 SILENT_ALPHA: smart money buying (Step 2) but zero social buzz — potential early signal
- ⚠️ HYPE_RISK: social score > 85 but smart money already selling (soldRatio > 60%) — possible exit liquidity
- 🧊 COLD: socialScore < 30 — no one is talking about this token
Step 4: Meme Coin Scan
Goal: Scan launchpads for new launches worth tracking.
4.1 New Token Scan
onchainos memepump tokens --chain 501
onchainos memepump tokens --chain 56
4.2 Extract Key Metrics
For each new meme token:
symbol, tokenAddress, bondingPercent (bonding curve progress)market.marketCapUsd, market.buyTxCount1h, market.sellTxCount1htags.snipersPercent, tags.bundlersPercenttags.top10HoldingsPercent, tags.devHoldingsPercent, tags.freshWalletsPercenttags.totalHolderssocial.x (has Twitter?), social.website, social.telegramcreatorAddress (for dev reputation lookup)
4.3 Developer Reputation Check
For promising tokens (survived bonding, has social presence):
onchainos memepump token-dev-info --address <tokenAddress> --chain <chainId>
Key fields:
devCreateTokenCount — how many tokens this dev has createddevRugPullTokenCount — how many ruggeddevLaunchedTokenCount — how many survived past bonding curve
4.4 Bundle/Sniper Detection
onchainos memepump token-bundle-info --address <tokenAddress> --chain <chainId>
4.5 Meme Scoring
Filter out garbage:
- Sniper % > 50% → likely bot-controlled → skip
- Top10 holdings > 60% → extreme concentration → skip
- 0 holders or < 3 holders → too early → skip
- No social presence at all → skip
- Dev has > 5 rug pulls → skip
Keep tokens that have:
- Survived bonding curve (migrated)
- Sniper < 20%, bundle < 10%
- Has at least Twitter presence
- Dev rug pull rate < 20%
- Growing holder count
Step 5: Security Audit
Goal: Batch security scan all candidate tokens from Steps 1-4.
5.1 Collect Candidates
Merge the shortlisted tokens from Steps 1, 2, 3, and 4 (deduplicate by address). Max 10 tokens for batch scan.
5.2 Batch Token Security Scan
onchainos security token-scan --tokens "<chainId1>:<addr1>,<chainId2>:<addr2>,..."
Up to 10 tokens per batch. Key fields to check:
riskLevel: LOW / MEDIUM / HIGHisHoneypot: true = INSTANT REJECTisMintable: true = can create infinite tokensisDumping: true = active sell pressureisFakeLiquidity: true = liquidity is fakeisLiquidityRemoval: true = LP being pulledisCounterfeit: true = fake/copycat tokenisWash: true = wash trading detected
5.3 Advanced Risk Analysis
For tokens that pass the security scan, run advanced info:
onchainos token advanced-info --address <address> --chain <chainId>
Key fields:
devCreateTokenCount — serial deployer?devRugPullTokenCount — rug historylpBurnedPercent — LP lock safety (higher = safer)sniperHoldingPercent — sniper concentrationbundleHoldingPercent — bundle bot concentrationsuspiciousHoldingPercent — flagged walletstokenTags — look for: communityRecognized, smartMoneyBuy, dsPaid, CTO
5.4 Risk Classification
| Risk Level | Criteria | Action |
|---|
| SAFE | LOW risk, no flags, LP burned > 90%, dev clean | Can consider |
| CAUTION | LOW risk but some flags (high dev token count, moderate concentration) | Small position only |
| DANGER | Any honeypot/mintable/fake liquidity flag | REJECT |
| CRITICAL | Multiple red flags, dev rug history, active dumping | REJECT + warn |
Step 6: Signal Backtesting (Historical Validation)
Goal: For BUY/WATCH candidates that passed security audit, validate the signal by checking historical price performance using DexPaprika OHLCV data.
6.1 Select Candidates for Backtesting
Only backtest tokens that:
- Passed Step 5 security audit (Risk = LOW or MEDIUM, no critical flags)
- Have a composite score > 45 from Steps 1-5 (skip obvious AVOIDs)
- Max 5 tokens to backtest (API rate limiting)
6.2 Get Token Pool (Highest Liquidity)
For each candidate, find the highest-liquidity DEX pool:
curl -s "https://api.dexpaprika.com/networks/<network>/tokens/<tokenAddress>/pools?limit=3"
Network mapping:
- Solana →
solana
- Base →
base
- Ethereum →
ethereum
- BSC →
bsc
- Arbitrum →
arbitrum-one
From results, pick the pool with highest volume_usd. Record pool_id.
6.3 Pull Historical OHLCV
curl -s "https://api.dexpaprika.com/networks/<network>/pools/<pool_id>/ohlcv?start=<30d_ago>&end=<today>&interval=24h&limit=30"
curl -s "https://api.dexpaprika.com/networks/<network>/pools/<pool_id>/ohlcv?start=<7d_ago>&end=<today>&interval=1h&limit=168"
Available intervals: 1m, 5m, 10m, 15m, 30m, 1h, 6h, 12h, 24h
6.4 Compute Signal Metrics
From OHLCV data, calculate:
Price Trend:
price_7d_change: 7-day price change %price_30d_change: 30-day price change %price_from_ath: distance from 30-day all-time high %price_from_atl: distance from 30-day all-time low %
Volatility:
daily_volatility: average daily (high-low)/open %max_drawdown_7d: worst peak-to-trough decline in 7 days
Volume Trend:
volume_trend: is 7d avg volume higher or lower than 30d avg? (expanding = bullish)volume_spike_days: days with volume > 3x average in last 30d
Support/Resistance:
current_vs_7d_vwap: current price relative to 7-day VWAP (above = bullish, below = bearish)consolidation_range: is price in a tight range (<10% spread) in last 3 days? (potential breakout)
6.5 Smart Money Entry Timing Analysis
If the token appeared in Step 2 (smart money signals), analyze:
- Where is the current price relative to when smart money likely entered?
- Did SM enter near recent lows (good timing) or near highs (chasing)?
- Is the token still within 20% of SM entry zone? (potential upside remains)
- Has SM already captured > 50% of the recent move? (late entry risk)
Estimate SM entry price by looking at the OHLCV around the signal detection time.
6.6 Backtest Scoring
Rate each token's historical performance:
| backtestScore | Criteria |
|---|
| 80-100 | Uptrend + expanding volume + near support + SM entered low |
| 60-79 | Mixed trend but positive volume + reasonable entry zone |
| 40-59 | Sideways/declining + no volume expansion |
| 20-39 | Downtrend + shrinking volume + SM entry near highs |
| 0-19 | Crash + extreme drawdown + volume collapse |
6.7 Backtest Signal Flags
- 📈 UPTREND: 7d change > +15%, expanding volume → momentum confirmed
- 🔄 CONSOLIDATION: tight range + volume drying up → potential breakout/breakdown
- 📉 DOWNTREND: 7d change < -20%, declining volume → avoid or wait for bottom
- 💎 DIAMOND_ENTRY: price within 10% of 30d low + volume expanding → potential reversal point
- 🏔️ NEAR_ATH: price within 10% of 30d high → late entry risk, wait for pullback
Step 7: Trend Monitoring & Alerts
Goal: Detect whether candidate tokens are trending on mainstream platforms BEFORE price pumps, and optionally push alerts via multi-channel notifications.
7.1 Determine Available Trend Sources
Check which trend monitoring tools are available:
Source priority (use all that work):
1. TrendRadar MCP → Chinese platforms (Zhihu, Weibo, Bilibili, Douyin, Baidu, etc.)
2. Google Trends MCP → Global search interest (worldwide + country-specific)
If neither is available, skip this step. Assign trendScore = 50 (neutral) for all tokens.
7.2 TrendRadar: Chinese Platform Trend Detection
TrendRadar provides trend data from 30+ Chinese platforms. For our use case:
Step A: Trigger a fresh crawl (if data is stale)
Tool: mcp__trendradar__trigger_crawl
Args: save_to_local = true
If crawl fails (no config), skip to cached data or Google Trends only.
Step B: Check global trending topics
Tool: mcp__trendradar__get_trending_topics
Args: top_n = 20, extract_mode = "auto_extract"
Scan the trending topic list for any crypto/blockchain/Web3 keywords. Note which narratives are hot on Chinese platforms (AI, meme, DeFi, etc.).
Step C: Search for each candidate token
For each candidate token (top 5 from Steps 1-5):
Tool: mcp__trendradar__search_news
Args: query = "<TOKEN_SYMBOL>", limit = 10
From results, extract:
- cnMentionCount: number of mentions on Chinese platforms
- cnPlatforms: which platforms mention it (Zhihu = informed community, Weibo = mass awareness, Bilibili = young community)
- cnSentiment: positive / negative / neutral ratio from titles
Step D: Analyze viral potential (if mentions found)
Tool: mcp__trendradar__analyze_topic_trend
Args: topic = "<TOKEN_SYMBOL>", analysis_type = "viral", spike_threshold = 3.0
Check for:
- spike_detected: is there a sudden surge in mentions?
- lifecycle_phase: emerging / growing / peak / declining
- heat_score: normalized heat score across platforms
Scoring:
- 5+ mentions across 3+ platforms, spike detected →
cnTrendScore = 90
- 3+ mentions, positive sentiment, growing phase →
cnTrendScore = 70
- 1-2 mentions, neutral sentiment →
cnTrendScore = 50
- Zero mentions →
cnTrendScore = 30 (Chinese community hasn't noticed yet)
7.3 Google Trends: Global Search Interest
Step A: Get currently trending topics
Tool: mcp__google-trends__google_trends_trending
Args: language = "en", country = "US"
Step B: Cross-check with candidate tokens
Scan the global trending topics list for:
- Exact token symbol matches (e.g., "TROLL", "PEPE")
- Related narrative keywords (e.g., "solana meme coin", "AI crypto")
- Broader crypto market trends (e.g., "bitcoin ATH", "crypto bull run")
Scoring:
- Token name appears in trending topics →
globalTrendScore = 95 (extremely bullish — mainstream attention)
- Related narrative is trending →
globalTrendScore = 70 (narrative tailwind)
- Crypto/blockchain terms trending →
globalTrendScore = 55 (general market interest)
- No crypto-related trends →
globalTrendScore = 40 (no mainstream tailwind)
7.4 Trend Score Calculation
Combine available trend sources:
If both TrendRadar + Google Trends available:
trendScore = cnTrendScore × 0.50 + globalTrendScore × 0.50
If only TrendRadar available:
trendScore = cnTrendScore
If only Google Trends available:
trendScore = globalTrendScore
If neither available:
trendScore = 50 (neutral)
7.5 Trend Signal Flags
- 🚀 TREND_SURGE: trendScore > 80, token found on BOTH Chinese platforms AND Google Trends — massive cross-market attention, move fast
- 📊 CN_BUZZ: cnTrendScore > 70 but globalTrendScore < 50 — hot on Chinese platforms, not yet global — potential early signal for Western markets
- 🌐 GLOBAL_TREND: globalTrendScore > 70 but cnTrendScore < 50 — global mainstream attention, Chinese community hasn't caught up yet
- 📡 EARLY_SIGNAL: 1-2 mentions found in trend analysis but not mainstream trending — very early, needs more confirmation
- 💤 NO_TREND: trendScore < 30 — not trending anywhere, may lack the catalyst for price action
7.6 Multi-Channel Alert Push (Optional — Post-Scan)
If BUY recommendations are found AND TrendRadar notification channels are configured:
Step A: Check available channels
Tool: mcp__trendradar__get_notification_channels
Step B: Format and send alert
Tool: mcp__trendradar__send_notification
Args:
title = "🔔 Daily Alpha Scanner — BUY Signal"
message = "<formatted BUY recommendations with scores>"
channels = [configured channels]
Alert content format:
**Daily Alpha Scanner v4.0 — BUY Alert**
🟢 **TOKEN_NAME** (Chain) — Score: XX/100
· MCap: $XXM | SM: X wallets | Social: XX | Backtest: 📈
· Trend: 🚀 TREND_SURGE — trending on Google + Chinese platforms
· Why: [1-line reason]
⏰ Scanned at: YYYY-MM-DD HH:MM UTC
Supported channels: Telegram, Feishu (飞书), Slack, DingTalk (钉钉), WeChat Work (企业微信), Email, ntfy, Bark
If no notification channels are configured, skip alerts. The report still contains all trend data.
Step 8: Consolidated Briefing
Goal: Synthesize all data into a single actionable report.
8.1 Report Structure
Use the template at templates/daily-briefing.md to generate the output.
8.2 Scoring Model (8 Dimensions)
Each candidate token gets a composite score (0-100):
| Factor | Weight | Data Source |
|---|
| Narrative strength | 8% | Step 1 categorization + current market meta |
| On-chain momentum | 8% | Price change, volume, tx count, holder growth |
| Smart money conviction | 25% | Step 2: signal count, wallet count, sold ratio |
| Social sentiment | 8% | Step 3: news + Reddit + Twitter combined socialScore |
| Security score | 25% | Step 5: security scan + advanced info |
| Historical validation | 8% | Step 6: DexPaprika OHLCV backtest — price trend, volume, entry timing |
| Trend monitoring | 10% | Step 7: TrendRadar Chinese platforms + Google Trends global search interest |
| Liquidity depth | 8% | Liquidity USD, liquidity/mcap ratio |
Signal Bonus/Penalty (Social + Backtest + Trend combined):
- If social signal = 🔥 VIRAL → add +5 bonus to final score
- If social signal = 🤫 SILENT_ALPHA → no change (early signal, not penalized)
- If social signal = ⚠️ HYPE_RISK → subtract -10 from final score (exit liquidity warning)
- If social signal = 🧊 COLD → subtract -3 from final score
- If backtest signal = 📈 UPTREND → add +3 bonus (momentum confirmed by history)
- If backtest signal = 💎 DIAMOND_ENTRY → add +5 bonus (price near bottom + volume expanding)
- If backtest signal = 📉 DOWNTREND → subtract -5 from final score
- If backtest signal = 🏔️ NEAR_ATH → subtract -3 from final score (late entry risk)
- If trend signal = 🚀 TREND_SURGE → add +5 bonus (cross-market trending)
- If trend signal = 📊 CN_BUZZ → add +3 bonus (Chinese community early signal)
- If trend signal = 🌐 GLOBAL_TREND → add +3 bonus (global mainstream interest)
- If trend signal = 📡 EARLY_SIGNAL → add +1 bonus (very early, minimal weight)
- If trend signal = 💤 NO_TREND → subtract -2 from final score (no catalyst)
8.3 Purchase Recommendation Tiers
Based on composite score and risk tolerance:
BUY (Score > 70, Security = SAFE)
- Strong narrative + smart money backing + clean security
- Suggested position: 2-5% of portfolio
WATCH (Score 50-70, Security = SAFE/CAUTION)
- Promising but needs more confirmation
- Set price alerts, monitor daily
AVOID (Score < 50 or Security = DANGER/CRITICAL)
- Too risky or no clear edge
- Explain specific red flags
8.4 Output Format
Generate the briefing with:
- Executive summary (3-5 bullets)
- Hot tokens by narrative table
- Smart money signal table
- Social sentiment overview (news + Reddit + Twitter summary per token)
- Meme scan highlights
- Security audit results
- Historical validation (price chart summary, backtest scores, entry timing)
- Trend monitoring (Chinese platform buzz + Google Trends + trend signals)
- Final recommendation table with 8D score breakdown and risk rating
- Alert push status (if notifications sent)
- Disclaimer
8.5 Save Report
mkdir -p reports
Error Handling
- If
onchainos returns error 50125 (region restriction): inform user to check API key region or use VPN
- If any step returns empty data: skip that step, note it in the report, continue with available data
- If security scan returns empty for a token: mark as "UNSCANNED" in the report, do NOT recommend
- Social sentiment graceful degradation: if opennews MCP unavailable → use Reddit + Twitter only; if Reddit blocked → use opennews + Twitter; if all social tools fail → assign socialScore = 50 (neutral) and note "Social data unavailable" in report
- If xreach times out (common without proxy): fall back to opentwitter-mcp or skip Twitter entirely
- DexPaprika graceful degradation: if API returns error or empty data → skip backtesting, assign backtestScore = 50 (neutral) and note "Historical data unavailable" in report
- If pool not found for a token (new token, no DEX history) → backtestScore = 50, note "No trading history"
- TrendRadar graceful degradation: if Docker container not running or MCP unreachable → skip Chinese platform trend check, use only Google Trends; if crawl fails (no config.yaml) → try using cached data via search_news; if no cached data → cnTrendScore = 50 (neutral)
- Google Trends graceful degradation: if MCP connection fails or timeout → skip global trend check, use only TrendRadar; if both fail → trendScore = 50 (neutral) and note "Trend data unavailable"
- Alert push graceful degradation: if send_notification fails or no channels configured → skip alerts, report still generated normally
- Always run all 8 steps even if some data is partial — the report should indicate data completeness per step
Quick Mode
If the user says "快速扫描" / "quick scan", run abbreviated version:
hot-tokens top 10 only (single chain)signal list smart money only (single chain)- Quick social scan: opennews only (skip Reddit/Twitter), top 5 tokens
- Skip meme scan
- Security scan top 5 candidates only
- Skip backtesting (quick mode does not run DexPaprika)
- Skip trend monitoring (quick mode does not run TrendRadar/Google Trends)
- Abbreviated 1-page briefing with 8D scores (backtest + trend = neutral)
If notification channels are configured, still push BUY alerts in quick mode
Chain Reference
| Chain | ID | Meme Support |
|---|
| Solana | 501 | pumpfun, believe, launchlab, moonshot, etc. |
| BSC | 56 | fourmeme, flap |
| Base | 8453 | clanker, bankr |
| Ethereum | 1 | Limited |
| TRON | 195 | sunpump |
