daily-alpha-scanner

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:

# 1. opennews MCP — crypto news sentiment (best source, MCP server)
#    If configured: mcp__opennews__search_news_by_coin tool is available
#    Install: see https://github.com/6551Team/opennews-mcp

# 2. Reddit JSON API — community buzz (no auth needed, works everywhere)
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"

# 3. xreach CLI — Twitter/X KOL tracking (needs proxy in China)
#    Configure proxy first: agent-reach configure proxy http://127.0.0.1:7890
which xreach && xreach search "test" --json -n 1 --proxy http://127.0.0.1:7890 2>/dev/null && echo "xreach: OK" || echo "xreach: unavailable"

# 4. opentwitter-mcp — Twitter MCP server (alternative to xreach)
#    If configured: opentwitter MCP tools are available

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)

# DexPaprika provides DEX historical OHLCV data by token contract address
# Supports Solana, Base, Ethereum, BSC, Arbitrum + 33 networks
# REST API — no installation needed, just curl

# Test:
curl -s "https://api.dexpaprika.com/search?query=TROLL" | python3 -c "import json,sys; print(json.loads(sys.stdin.read()).get('tokens',[])[0])"

# Optional: add as MCP server for richer integration
# claude mcp add dexpaprika -- npx -y dexpaprika-mcp

If DexPaprika API is unreachable, Step 6 is skipped and backtestScore defaults to 50 (neutral).

Trend Monitoring: TrendRadar + Google Trends (graceful degradation — both optional)

# 1. TrendRadar MCP — Chinese platform trend monitoring (Docker)
#    Crawls Zhihu, Weibo, Bilibili, Douyin, Baidu etc. for trending topics
#    Also provides multi-channel alert push (Telegram/Feishu/Slack/DingTalk/WeChat)
#    Install: docker run -d --name trendradar-mcp -p 8788:3333 wantcat/trendradar-mcp
#    Add to Claude: claude mcp add trendradar --transport http -- http://localhost:8788/mcp
#    GitHub: https://github.com/WantCat/TrendRadar (58K+ stars)

# 2. Google Trends MCP — global search interest tracking
#    Detects rising search interest for token names worldwide
#    Install: claude mcp add google-trends -- npx -y @andrewlwn77/google-trends-mcp

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:

# Trending by OKX trending score (hot-tokens ranking)
onchainos token hot-tokens --chain <chainId> --limit 20

# Volume-based trending (complementary view)
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, chainIndex
• price, change (24h %), volume, marketCap, liquidity
• holders, top10HoldPercent, bundleHoldPercent, devHoldPercent
• riskLevelControl (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:

# Smart money buy signals
onchainos signal list --chain <chainId> --wallet-type 1 --limit 10

# KOL buy signals
onchainos signal list --chain <chainId> --wallet-type 2 --limit 10

# Whale buy signals
onchainos signal list --chain <chainId> --wallet-type 3 --limit 10

2.2 Extract Signal Data

For each signal entry:

• token.symbol, token.tokenAddress, token.marketCapUsd
• triggerWalletCount (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:

# Search across crypto Reddit
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

# Latest meme launches on Solana
onchainos memepump tokens --chain 501

# Latest meme launches on BSC (if in target chains)
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.sellTxCount1h
• tags.snipersPercent, tags.bundlersPercent
• tags.top10HoldingsPercent, tags.devHoldingsPercent, tags.freshWalletsPercent
• tags.totalHolders
• social.x (has Twitter?), social.website, social.telegram
• creatorAddress (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 created
• devRugPullTokenCount — how many rugged
• devLaunchedTokenCount — 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 / HIGH
• isHoneypot: true = INSTANT REJECT
• isMintable: true = can create infinite tokens
• isDumping: true = active sell pressure
• isFakeLiquidity: true = liquidity is fake
• isLiquidityRemoval: true = LP being pulled
• isCounterfeit: true = fake/copycat token
• isWash: 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 history
• lpBurnedPercent — LP lock safety (higher = safer)
• sniperHoldingPercent — sniper concentration
• bundleHoldingPercent — bundle bot concentration
• suspiciousHoldingPercent — flagged wallets
• tokenTags — 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

# 30-day daily candles
curl -s "https://api.dexpaprika.com/networks/<network>/pools/<pool_id>/ohlcv?start=<30d_ago>&end=<today>&interval=24h&limit=30"

# 7-day hourly candles (for recent price action)
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:

1. Executive summary (3-5 bullets)
2. Hot tokens by narrative table
3. Smart money signal table
4. Social sentiment overview (news + Reddit + Twitter summary per token)
5. Meme scan highlights
6. Security audit results
7. Historical validation (price chart summary, backtest scores, entry timing)
8. Trend monitoring (Chinese platform buzz + Google Trends + trend signals)
9. Final recommendation table with 8D score breakdown and risk rating
10. Alert push status (if notifications sent)
11. Disclaimer

8.5 Save Report

# Save to reports directory
mkdir -p reports
# Filename: daily-alpha-YYYY-MM-DD.md

---

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:

1. hot-tokens top 10 only (single chain)
2. signal list smart money only (single chain)
3. Quick social scan: opennews only (skip Reddit/Twitter), top 5 tokens
4. Skip meme scan
5. Security scan top 5 candidates only
6. Skip backtesting (quick mode does not run DexPaprika)
7. Skip trend monitoring (quick mode does not run TrendRadar/Google Trends)
8. 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