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: ```bash 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: ```bash # 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: ```bash # 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: Meme Coin Scan **Goal**: Scan launchpads for new launches worth tracking. ### 3.1 New Token Scan ```bash # 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.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): ```bash 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 ```bash 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 ```bash 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: ```bash 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: 1. Executive summary (3-5 bullets) 2. Hot tokens by narrative table 3. Smart money signal table 4. Meme scan highlights 5. Security audit results 6. Final recommendation table with risk rating 7. Disclaimer ### 5.5 Save Report ```bash # 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 - 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: 1. `hot-tokens` top 10 only (single chain) 2. `signal list` smart money only (single chain) 3. Skip meme scan 4. Security scan top 5 candidates only 5. 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 |