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ru7superbeauty

binance-square-skill

by RU7superbeauty · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install binance-square-skill
Description
Binance Square (币安广场) signal agent. Scrapes 200+ posts via Puppeteer + API interception, detects bot-pushed narratives, runs on-chain confirmation (OI/fundin...
README (SKILL.md)

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)

Var Purpose Effect if missing
COINGLASS_BASE Coinglass API or proxy base URL (e.g. https://your-proxy/api) Step 2 (on-chain) is skipped, direction calls degrade
TG_BOT_TOKEN Telegram bot token from @BotFather scan:tg mode skips the push, returns the message text instead
TG_CHAT_ID Telegram chat ID (use @userinfobot) Same as above
CHROME_PATH Override Chrome binary path Auto-detected (Win/Mac/Linux + Edge fallback)

Modes (dispatch on $ARGUMENTS)

Input Action
scan (default if no args) Full pipeline: scrape feed + drill top 3 coins + direction judgment
scan:tg Same as scan plus Telegram DM push (requires TG env vars)
coin:RAVE Deep-drill a specific coin's hashtag page (~200 posts)
read:URL Read and summarize a single Binance Square article
read:KEYWORD Search 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 \x3C -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 (\x3C4000 chars) to a temp file:

cat > /tmp/tg-signal.txt \x3C\x3C'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 \x3C 200 → BOT_SUSPECT
  • Any author with 5+ posts + avg views \x3C 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.

Usage Guidance
This skill appears coherent with its purpose, but review these practical safety points before running: - Review the included code (scrape-square.mjs and send-telegram.mjs) yourself — they are the only executable files and are readable (no obfuscated code was found). - COINGLASS_BASE: only provide an API base URL you trust. If you point this to a third-party proxy, that proxy will receive all coinglass queries and any API key you include there may be exposed. - Telegram creds: TG_BOT_TOKEN and TG_CHAT_ID are sensitive (bot token grants message-sending power). Only set them if you trust the skill and the host environment. Prefer creating a dedicated bot and chat for testing. - Network activity: the scraper launches Puppeteer and intercepts internal Binance API responses. This generates web traffic to Binance and to your COINGLASS_BASE and to api.telegram.org. If you need to limit exposure, run inside an isolated environment (container or VM) or inspect network traffic first. - Installation: npm install will pull puppeteer-core and its transitive deps. Ensure you run this in a controlled environment and have compatible Node/Chrome versions (or set CHROME_PATH). - Legal/ToS: scraping undocumented internal APIs may violate Binance terms of service; consider legal/compliance implications before automated runs. - Testing: use the provided test modes (e.g., send-telegram.mjs --test and smaller --scrolls values) to validate behavior before full runs. If you want extra caution: run the skill in a disposable container, avoid supplying long-lived or high-privilege credentials, and point COINGLASS_BASE to your own proxy that you control so you can audit requests.
Capability Analysis
Type: OpenClaw Skill Name: binance-square-skill Version: 1.0.0 The skill implements a complex trading signal pipeline using Puppeteer for API interception on Binance Square and shell-based curl commands for market data retrieval. While the behavior is aligned with its stated purpose, it utilizes high-risk capabilities such as executing shell commands (SKILL.md), searching for local browser binaries via execSync (scrape-square.mjs), and writing to the filesystem. Additionally, the skill is susceptible to indirect prompt injection because it scrapes untrusted content from a public social platform and instructs the AI agent to summarize and act upon it without explicit sanitization or safety warnings.
Capability Tags
crypto
Capability Assessment
Purpose & Capability
Name/description (scrape Binance Square, run Coinglass checks, optionally push to Telegram) match the declared requirements: Node to run the provided scripts, curl referenced for Coinglass calls, and TG env vars for Telegram pushes. No unrelated secrets or binaries are requested.
Instruction Scope
SKILL.md instructs installing npm deps (puppeteer-core), running the provided Node scripts which intercept Binance Square API responses, perform local processing, write JSON/markdown reports under the skill directory, and optionally POST to Telegram or curl a user-provided Coinglass base URL. The instructions do not ask the agent to read unrelated system files or exfiltrate credentials beyond the declared env vars.
Install Mechanism
No automated install spec — user must run `npm install` to install puppeteer-core. This is expected for a Puppeteer-based scraper but pulls a sizable dependency and may require a compatible Node runtime and a matching Chrome/Chromium. No arbitrary remote binary downloads or obscure URLs are used by the skill itself.
Credentials
Required env vars (COINGLASS_BASE, TG_BOT_TOKEN, TG_CHAT_ID) are proportional to the claimed features: on-chain lookups and optional Telegram pushes. These are sensitive values but justified by the feature set. No additional unrelated credentials are requested.
Persistence & Privilege
Skill is not always-enabled and doesn't request system-wide privileges. It writes reports and JSON into its own skill directory (~/.claude/skills/binance-square/) and does not modify other skills or global agent config. Autonomous invocation is allowed (platform default) but not elevated by the skill.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install binance-square-skill
  3. After installation, invoke the skill by name or use /binance-square-skill
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Binance Square Signal Agent v1.0.0 - Provides an end-to-end pipeline for detecting crypto trade signals based on Binance Square narrative tracking and on-chain confirmation. - Scrapes 200+ Binance Square posts using Puppeteer with multi-method bot detection. - Runs on-chain confirmation steps for each coin via user-supplied Coinglass API/proxy (OI, funding rates, liquidations). - Combines four signal sources (liquidation, funding, OI/price, Square sentiment) for actionable LONG/SHORT/AVOID/WATCH calls. - Generates detailed markdown reports and optionally pushes summary signals to Telegram (configurable via environment variables). - Supports multiple modes: full scan, Telegram push, deep coin drill, and keyword/article summary.
Metadata
Slug binance-square-skill
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is binance-square-skill?

Binance Square (币安广场) signal agent. Scrapes 200+ posts via Puppeteer + API interception, detects bot-pushed narratives, runs on-chain confirmation (OI/fundin... It is an AI Agent Skill for Claude Code / OpenClaw, with 94 downloads so far.

How do I install binance-square-skill?

Run "/install binance-square-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is binance-square-skill free?

Yes, binance-square-skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does binance-square-skill support?

binance-square-skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created binance-square-skill?

It is built and maintained by RU7superbeauty (@ru7superbeauty); the current version is v1.0.0.

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