binance-square

Binance Square (币安广场) signal agent. Scrapes 200+ posts via Puppeteer + API interception, detects bot-pushed narratives, runs on-chain confirmation (OI/funding/liquidation via Coinglass), and produces directional trade signals (LONG/SHORT/AVOID). Optionally pushes signal reports to Telegram. Triggers on mentions of "binance square", "广场信号", "MM 信号", "做市商扫描", crypto narrative tracking, or trading signal generation.

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Install skill "binance-square" with this command: npx skills add ru7superbeauty/binance-square-skill

Binance Square Signal Agent

End-to-end trading signal pipeline built on the thesis that market makers seed narratives on Binance Square before / during accumulation. Square is the largest unblocked Chinese crypto info source — tracking narrative flow there is the sentiment equivalent of tracking on-chain fund flow.

First-Time Setup

The skill ships with two Node.js scripts that need puppeteer-core installed once. After ClawHub installs this skill to ~/.claude/skills/binance-square/, run:

cd ~/.claude/skills/binance-square && npm install

Then verify Chrome/Chromium is installed (auto-detected on Win/Mac/Linux). Override with CHROME_PATH env var if needed.

Optional Configuration (env vars)

VarPurposeEffect if missing
COINGLASS_BASECoinglass API or proxy base URL (e.g. https://your-proxy/api)Step 2 (on-chain) is skipped, direction calls degrade
TG_BOT_TOKENTelegram bot token from @BotFatherscan:tg mode skips the push, returns the message text instead
TG_CHAT_IDTelegram chat ID (use @userinfobot)Same as above
CHROME_PATHOverride Chrome binary pathAuto-detected (Win/Mac/Linux + Edge fallback)

Modes (dispatch on $ARGUMENTS)

InputAction
scan (default if no args)Full pipeline: scrape feed + drill top 3 coins + direction judgment
scan:tgSame as scan plus Telegram DM push (requires TG env vars)
coin:RAVEDeep-drill a specific coin's hashtag page (~200 posts)
read:URLRead and summarize a single Binance Square article
read:KEYWORDSearch Square for a keyword and summarize top results

Pipeline: scan and scan:tg

Step 1 — Scrape

node ~/.claude/skills/binance-square/scrape-square.mjs --drill --top 3 --scrolls 25 --pages 10

The scraper writes a square-YYYY-MM-DD-HHmm.json file in its own directory by default. Override with --out PATH. Read the JSON output. Key fields per coin in coinRanking:

  • mentions, botPct, verifiedPosts
  • sentiment.label (BULLISH / BEARISH / NEUTRAL), sentiment.score, sentiment.bullish, sentiment.bearish
  • views, likes

drillResults[COIN] contains the same breakdown for each drilled hashtag page (larger sample, bot-dense — this is where coordinated narrative pushes are visible).

Step 2 — On-chain confirmation (skip if COINGLASS_BASE not set)

For each non-baseline coin (not BTC/ETH/BNB/SOL/XRP/DOGE) with 2+ feed mentions:

curl -s "$COINGLASS_BASE/coinglass?type=oi-exchanges&symbol=COIN"
curl -s "$COINGLASS_BASE/coinglass?type=funding-exchanges&symbol=COIN"
curl -s "$COINGLASS_BASE/coinglass?type=liquidation"

Extract:

  • OI: total.chg24h (24h OI change %)
  • Funding: average rate across major exchanges (Binance / Bybit / OKX)
  • Liquidation: long24h vs short24h USD per coin
  • Price 24h: from gainers (Step 3) or derive from OI deltas

The user must provide their own COINGLASS_BASE URL — either the official Coinglass API with their key, or their own proxy. Without this, direction judgment falls back to Square sentiment + price action only.

Step 3 — Gainers cross-reference

WebFetch https://www.binance.com/zh-CN/markets/coinInfo — extract 领涨榜 (top gainers) with 24h% change.

Step 4 — Direction judgment

Combine the four signal sources for each candidate coin:

Signal weights (strongest first):

  1. Liquidation ratio  → strongest (actual money flow)
     short_liq >> long_liq  → LONG (short squeeze in progress)
     long_liq >> short_liq  → SHORT (long cascade in progress)

  2. Funding extreme    → contrarian signal
     rate < -0.10%       → LONG bias (shorts overcrowded)
     rate > +0.10%       → SHORT bias (longs overcrowded)

  3. OI + Price         → momentum / divergence
     OI↑ price↑          → momentum continuation
     OI↑ price flat      → pre-positioning, watch breakout direction
     OI↑ price↓          → short building (may squeeze)
     OI↓ price↓          → long liquidation cascade

  4. Square sentiment   → contrarian indicator (with bot quality filter)
     Retail BEAR + funding negative + OI rising → MM accumulating vs retail → LONG
     Retail BULL + bot% > 40%                   → bot-pushed pump → AVOID
     Retail BULL organic (low bot%) + rising price → trend follow LONG

Direction call: LONG ✅ / SHORT 🔻 / AVOID ⚠️ / WATCH 👀

  • WATCH for OI divergence with unclear direction
  • AVOID for bot-dominated noise or event-driven moves (FUD / hack / legal)

Step 5 — Save full report

Write detailed markdown report to ~/.claude/skills/binance-square/reports/signal-YYYY-MM-DD-HHmm.md (create the reports/ dir if needed). Include:

  • Candidates table (coin, posts, bot%, sentiment, OI, funding, liq ratio, direction)
  • Per-coin direction rationale
  • Drill bot breakdown
  • Gainers cross-ref
  • Risk notes

Step 6 — Telegram push (only if scan:tg and TG env vars set)

Write condensed summary (<4000 chars) to a temp file:

cat > /tmp/tg-signal.txt <<'EOF'
*广场信号* YYYY-MM-DD HH:MM

*Feed* (N posts, X% bot)
COIN: N mentions, BEAR/BULL | ...

*Drill Bot%*
#COIN: N posts, X% bot, sentiment Y

*方向判断*
COIN: *LONG/SHORT/AVOID* [emoji]
  OI +X% | Funding X% | Liq 多M:空M | 广场 BEAR/BULL
  理由: [one sentence]

*涨幅榜* TOP1 +X% | TOP2 +X%
EOF

node ~/.claude/skills/binance-square/send-telegram.mjs --file /tmp/tg-signal.txt

If TG_BOT_TOKEN or TG_CHAT_ID env var is missing, skip this step and return the message text in the response instead.


Mode: coin:TICKER

Deep-drill a specific coin's topic page (~200 posts vs ~20 on main feed):

node ~/.claude/skills/binance-square/scrape-square.mjs --coin TICKER --pages 10

Then run Step 2 (on-chain) + Step 4 (direction) for just this coin. Report:

#TICKER deep dive — N posts scanned

Bot activity: X% bot (top bot authors: ...)
Sentiment: BULL / BEAR / NEUTRAL  (N bull / N bear / N neutral)
OI 24h: +X%   |   Funding: X%   |   Liq L:S
Price 24h: +X%

Direction: LONG / SHORT / AVOID — [reason]

Top 3 sample posts: ...

Mode: read:URL or read:KEYWORD

URL form (read:https://www.binance.com/...)

WebFetch the article. Extract: title, author, publish time, content, engagement, coin mentions, hashtags. Flag author if username matches Square-Creator-xxx → potential bot.

Keyword form (read:RAVE 爆仓)

WebSearch site:binance.com/square KEYWORD, then WebFetch top 3-5 results. For each, extract summary + sentiment + author type. Aggregate: overall sentiment, bot %, narrative theme.


Bot Detection (built into scraper)

Layer 1 (username pattern):

  • Display name matches /^Square-Creator-[a-f0-9]+$/ → BOT_SUSPECT (never customized profile)
  • Otherwise → tentatively LIKELY_HUMAN

Layer 2 (behavioral, post-hoc):

  • Default username (square-creator-* profile ID) + 3+ posts in batch + avg views < 200 → BOT_SUSPECT
  • Any author with 5+ posts + avg views < 100 → BOT_SUSPECT (catches custom-named bots)

Sentiment scoring only counts non-bot posts to avoid contamination.

The drill mode reveals bot rings — accounts that appear across multiple coin hashtags with high post counts and low engagement = signature of coordinated narrative promotion.


Output Contract

Return to main agent (concise — full detail lives in the saved report):

  1. Top 3 actionable signals with direction (LONG/SHORT/AVOID) + one-sentence rationale each
  2. Path to full saved report
  3. If scan:tg: confirmation of TG send with message_id, OR the message text + note that env vars weren't configured
  4. Critical anomalies: new coin trending, extreme funding rate, bot farm coordination

Disclaimer

This tool finds patterns. It is not financial advice. Trading decisions and risk management are entirely the user's responsibility. Past pattern correlations do not predict future moves.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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