| name | daily-alpha-scanner |
| description | One-click daily alpha scanner that runs a full 5-step on-chain research pipeline using OKX OnchainOS: (1) Hot Token Discovery with narrative categorization (AI, Meme, DeFi, Infra), (2) Smart Money / KOL / Whale buy-signal tracking with sold-ratio scoring, (3) Meme Coin launchpad scanning (pump.fun, fourmeme) with dev reputation and bundle/sniper detection, (4) Batch security audit (honeypot, mintable, fake LP, wash trading), (5) Consolidated briefing with 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. |
| 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":"1.0.0","homepage":"https://github.com/zhuyansen/daily-alpha-scanner"} |
Daily Alpha Scanner
A systematic 5-step pipeline that scans on-chain data across multiple chains and produces a consolidated briefing with purchase recommendations.
Pipeline
Step 1: Hot Tokens → Step 2: Smart Money → Step 3: Meme Scan
↓ ↓ ↓
Step 4: Security Audit (batch scan all candidates)
↓
Step 5: Consolidated Briefing + Purchase Recommendations
Prerequisites
Verify before starting:
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)
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, 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:
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.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: Meme Coin Scan
Goal: Scan launchpads for new launches worth tracking.
3.1 New Token Scan
onchainos memepump tokens --chain 501
onchainos memepump tokens --chain 56
3.2 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)
3.3 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
3.4 Bundle/Sniper Detection
onchainos memepump token-bundle-info --address <tokenAddress> --chain <chainId>
3.5 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 4: Security Audit
Goal: Batch security scan all candidate tokens from Steps 1-3.
4.1 Collect Candidates
Merge the shortlisted tokens from Steps 1, 2, and 3 (deduplicate by address). Max 10 tokens for batch scan.
4.2 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
4.3 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
4.4 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 5: Consolidated Briefing
Goal: Synthesize all data into a single actionable report.
5.1 Report Structure
Use the template at templates/daily-briefing.md to generate the output.
5.2 Scoring Model
Each candidate token gets a composite score (0-100):
| Factor | Weight | Data Source |
|---|
| Narrative strength | 15% | Step 1 categorization + current market meta |
| On-chain momentum | 20% | Price change, volume, tx count, holder growth |
| Smart money conviction | 25% | Signal count, wallet count, sold ratio |
| Security score | 25% | Security scan + advanced info |
| Liquidity depth | 15% | Liquidity USD, liquidity/mcap ratio |
5.3 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
5.4 Output Format
Generate the briefing with:
- Executive summary (3-5 bullets)
- Hot tokens by narrative table
- Smart money signal table
- Meme scan highlights
- Security audit results
- Final recommendation table with risk rating
- Disclaimer
5.5 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
- Always run all 5 steps even if some data is partial — the report should indicate data completeness
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)
- Skip meme scan
- Security scan top 5 candidates only
- Abbreviated 1-page briefing
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 |