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:
# 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,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:
# 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.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: Meme Coin Scan
Goal: Scan launchpads for new launches worth tracking.
3.1 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
3.2 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)
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 createddevRugPullTokenCount— how many ruggeddevLaunchedTokenCount— 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 / 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
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 historylpBurnedPercent— LP lock safety (higher = safer)sniperHoldingPercent— sniper concentrationbundleHoldingPercent— bundle bot concentrationsuspiciousHoldingPercent— flagged walletstokenTags— 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
# Save to reports directory
mkdir -p reports
# Filename: daily-alpha-YYYY-MM-DD.md
Error Handling
- If
onchainosreturns 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-tokenstop 10 only (single chain)signal listsmart 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 |