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docs: add Core Concepts, AI Agent install guide, and workflow docs
- README: add Quick Start (AI Agent) section with step-by-step key generation and .env configuration guidance; add Upgrade (AI Agent) section - README.zh.md: sync all changes from English README - skills/gmgn-market: add Core Concepts (10 terms: volume/amount distinction, rug_ratio, smart_degen_count, hot_level, renounced authorities, honeypot, creator_token_status, cto_flag, trenches lifecycle, wash/rat/bundler signals); add "Do NOT guess fields" IMPORTANT rule - skills/gmgn-portfolio: add Core Concepts (7 terms: realized/unrealized profit, profit_change multiplier, pnl ratio, winrate, cost vs usd_value, pagination); complete Response Field Reference tables for holdings/activity/stats - skills/gmgn-swap: add Core Concepts (8 terms: smallest unit, slippage decimal, amount vs percent mutex, currency tokens, anti-MEV, critical auth, order polling, filled amount conversion); add "Do NOT guess fields" IMPORTANT rule - skills/gmgn-track: add Core Concepts (8 terms: follow-wallet vs kol vs smartmoney, KOL vs smart_degen, is_open_or_close divergence, price_change ratio, base/quote address, tags array, cluster signal); add Safety Constraints section; add Output Format section; add "Do NOT guess fields" IMPORTANT rule - skills/gmgn-token: add --amount/--percent and --slippage/--auto-slippage mutex rules; add --tag + --order-by valid combination guide table for traders - src/index.ts: add track to CLI description - docs/token-due-diligence.md: new — full 4-step token due diligence workflow - docs/market-discover-opportunities.md: new — market discovery workflow Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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# Discover Trading Opportunities via Trending — Workflow
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Use this workflow to surface high-potential tokens from trending data.
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## Step 1 — Fetch trending data
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Fetch a broad pool with safe filters:
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```bash
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gmgn-cli market trending \
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--chain <chain> --interval 1h \
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--order-by volume --limit 50 \
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--filter not_honeypot --filter has_social --raw
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```
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## Step 2 — AI multi-factor analysis
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Analyze each record in the response using the following signals (apply judgment, not rigid rules):
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| Signal | Field(s) | Weight | Notes |
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|--------|----------|--------|-------|
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| Smart money interest | `smart_degen_count`, `renowned_count` | High | Key conviction indicator |
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| Bluechip ownership | `bluechip_owner_percentage` | Medium | Quality of holder base |
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| Real trading activity | `volume`, `swaps` | Medium | Distinguishes genuine interest from wash trading |
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| Price momentum | `change1h`, `change5m` | Medium | Prefer positive, non-parabolic moves |
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| Pool safety | `liquidity` | Medium | Low liquidity = high slippage risk |
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| Token maturity | `creation_timestamp` | Low | Avoid tokens less than ~1h old unless other signals are very strong |
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Select the **top 5** tokens with the best composite profile. Prefer tokens that perform well across multiple signals rather than excelling in just one.
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## Step 3 — Present top 5 to user
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Present results as a concise table, then give a one-line rationale for each pick:
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```
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Top 5 Trending Tokens — SOL / 1h
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# | Symbol | Address (short) | Smart Degens | Volume | 1h Chg | Reasoning
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1 | ... | ... | ... | ... | ... | Smart money accumulating + high volume
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2 | ...
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...
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```
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## Step 4 — Follow-up actions
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For each token, offer:
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- **Deep dive**: `token info` + `token security` for full due diligence (see [token-due-diligence.md](token-due-diligence.md))
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- **Swap**: execute directly if the user is satisfied with the trending data alone
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# Full Token Due Diligence — 4-Step Workflow
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Use this workflow before deciding to buy a token. Run all four steps in sequence.
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## Step 1 — Get basic info
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```bash
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gmgn-cli token info --chain sol --address <token_address> --raw
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```
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Check: `price`, `liquidity`, `holder_count`, `wallet_tags_stat.smart_wallets`, `wallet_tags_stat.renowned_wallets`, `link.website` / `link.twitter_username` / `link.telegram`.
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**Red flags**: all `link.*` social fields empty, very low liquidity (<$10k), zero `wallet_tags_stat.smart_wallets` and `renowned_wallets`.
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## Step 2 — Check security
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```bash
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gmgn-cli token security --chain sol --address <token_address> --raw
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```
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Check these fields and their safe thresholds:
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| Field | Safe | Warning | Danger |
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|-------|------|---------|--------|
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| `is_honeypot` | `"no"` | — | `"yes"` → Do not buy |
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| `open_source` | `"yes"` | `"unknown"` | `"no"` |
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| `owner_renounced` | `"yes"` | `"unknown"` | `"no"` |
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| `renounced_mint` (SOL) | `true` | — | `false` → mint risk |
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| `renounced_freeze_account` (SOL) | `true` | — | `false` → freeze risk |
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| `buy_tax` / `sell_tax` | `0` | `0.01–0.05` | `>0.10` → high tax |
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| `top_10_holder_rate` | `<0.20` | `0.20–0.40` | `>0.50` → whale risk |
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| `rug_ratio` | `<0.10` | `0.10–0.30` | `>0.30` → high rug risk |
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| `creator_token_status` | `creator_close` | — | `creator_hold` → dev not sold |
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| `sniper_count` | `<5` | `5–20` | `>20` → heavily sniped |
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## Step 3 — Check liquidity pool
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```bash
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gmgn-cli token pool --chain sol --address <token_address> --raw
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```
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Check: liquidity amount, which DEX (`exchange`), pool age (`creation_timestamp`). Low liquidity means high slippage risk when buying or selling.
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## Step 4 — Check smart money signals
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```bash
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# Is smart money accumulating?
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gmgn-cli token holders --chain sol --address <token_address> \
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--tag smart_degen --order-by buy_volume_cur --direction desc --limit 20 --raw
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# Have KOLs already taken profit?
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gmgn-cli token traders --chain sol --address <token_address> \
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--tag renowned --order-by profit --direction desc --limit 20 --raw
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```
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**Bullish signals**: smart_degen wallets buying heavily, unrealized_profit is large (still holding), renowned wallets accumulating, low sell_volume_cur.
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**Bearish signals**: sell_volume_cur > buy_volume_cur for smart money, large realized profits already taken (they may be done), top holders with very high amount_percentage starting to sell.
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