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1m Trade

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LeoYeAI
1m-trade

Integrated on-chain operations hub: integrates BlockBeats market intelligence, Hyperliquid DEX trading via `hl1m`, wallet creation and management at https://www.1m-trade.com, and supports local initialization using `hl1m init-wallet` (wallet address + proxy private key, never use the main wallet private key). Supports fully autonomous AI trading.

Overview

PublisherLeoYeAI
Repositoryopenclaw-master-skills
Skill name1m-trade
Stars
2.1K
Forks
325
Bundled files
11
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by LeoYeAI on GitHub. Read the source before you install it.

Installation

Install the 1m Trade AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git /tmp/openclaw-master-skills
mkdir -p .claude/skills
cp -r /tmp/openclaw-master-skills/skills/1m-trade .claude/skills/1m-trade
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 1m Trade in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 1m Trade on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 1m Trade is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

1m-trade Aggregator - On-chain Operations Hub

Official website (wallet & account): https://www.1m-trade.com

After first install

Scan and verify all required dependencies for sub-skills and install what is needed. From this skill bundle root, run node auto_check.js to verify required binaries and .env entries (it does not print secrets).

1m-trade-news (required)

This aggregator must have the 1m-trade-news sub-skill available: market intelligence, news, and BlockBeats API calls all go through it. Do not skip this step when installing the bundle.

  1. Skill files: Ensure the bundle includes skills/1m-trade-news/ (SKILL.md, etc.) and that your OpenClaw / host loads that folder as the 1m-trade-news skill.

  2. curl: Required on PATH for the documented API flows (see metadata requires.bins).

  3. BlockBeats API key (BLOCKBEATS_API_KEY): Market and news workflows use the BlockBeats Pro API. Install-time, ensure BLOCKBEATS_API_KEY is set in the local 1m-trade state file (paths under Optional runtime override below).

    Apply for / obtain a key (free tier):

    1. Request a free API key:
      bash
      curl --request GET --url "https://api-pro.theblockbeats.info/v1/api-key/free"
    2. From the JSON body, read data.api_key and use it as BLOCKBEATS_API_KEY.
    3. Write it to ~/.openclaw/.1m-trade/.env (or $OPENCLAW_STATE_DIR/.1m-trade/.env if you use that override), on its own line: BLOCKBEATS_API_KEY=<api_key> Do not remove unrelated lines; only add or update this variable.

Reference: skills/1m-trade-news/SKILL.mdGet an API key (includes agent-safe steps to populate .env without printing the key).

Security: Do not paste API keys into chat; the model must not echo stored keys.

1m-trade-dex (required)

This aggregator must have the 1m-trade-dex sub-skill available: trading, wallet queries, and hl1m all go through it. Do not skip this step when installing the bundle.

  1. Skill files: Ensure the bundle includes skills/1m-trade-dex/ (SKILL.md, reference.md, etc.) and that your OpenClaw / host loads that folder as the 1m-trade-dex skill.
  2. CLI (hl1m): Install the 1m-trade package so hl1m is on PATH (Python 3.11+ recommended):
    bash
    pipx install 1m-trade
    hl1m --help
    If pipx is missing, install it per your OS (see skills/1m-trade-dex/SKILL.mdSetup).
  3. Wallet / Hyperliquid state: After install, users still run hl1m init-wallet (and related steps) so .env contains the Hyperliquid fields auto_check.js expects — see skills/1m-trade-dex/SKILL.mdWallet initialization.

Optional runtime override:

  • OPENCLAW_STATE_DIR can be set to change where local .1m-trade state files are read/written.
  • If not set, tools default to ~/.openclaw/.1m-trade/.

Secret source-of-truth policy:

  • API key and wallet credentials are expected in the local state .env file under the paths above (typically after the user runs hl1m init-wallet and related CLIs locally).
  • Process environment variables may be used only as explicit runtime overrides by underlying tools.
  • LLM boundary: The model must not read .env into context or quote stored secrets. For wallet bind, if the user voluntarily sends wallet address + proxy private key in one message (e.g. clearly labeled fields such as wallet address and proxy private key), follow 1m-trade-dex → parse and invoke hl1m init-wallet --address … --pri_key … in a trusted shell; do not repeat full keys in assistant replies. Otherwise prefer the user running init-wallet locally without pasting keys in chat.
  • Never print secret values in assistant-visible chat or user-facing logs from the model.

Overview

This skill (1m-trade) is an orchestration hub that integrates multiple sub-skills into a single coherent workflow. You describe your goal (e.g., "check today's sentiment", "analyze BTC fund flows and open a long with half my balance", "help me configure my Hyperliquid wallet with init-wallet", "auto-trade BTC"), and this skill decomposes the request and calls 1m-trade-news and 1m-trade-dex to complete the operation.

Core workflows

Based on intent keywords, this skill routes into one of the workflows below (or composes them).

Workflow 1: Market intelligence (Data & News)

Triggers: market, price, news, macro, fund flows, perps, search [keyword]

Skill: 1m-trade-news

Logic:

  1. Parse the user query and map it to a scenario / intent mapping.
  2. Call the relevant BlockBeats API endpoints in parallel.
  3. Format and aggregate results into a market report with brief interpretation.

Example output:

📰 Market Report · 202X-XX-XX
===
1. 📊 Snapshot
   Sentiment: 35 → Neutral
   BTC ETF: +$120M net inflow today
   On-chain tx volume: +15% vs yesterday

2. 💰 Hot flows (Solana)
   1. JTO net inflow $4.2M
   2. ...

3. 🌐 Macro
   Global M2: +4.5% YoY → Liquidity easing
   DXY: 104.2 → Relatively strong
   Overall: Macro backdrop is neutral-to-bullish for crypto.

Workflow 2: Wallet setup (initialization)

Triggers: init wallet, configure wallet, configure trading account, bind wallet, connect Hyperliquid, set up trading, wallet settings, proxy key, API key (wallet); same message with both wallet address and proxy private key (or non-English equivalents per 1m-trade-dex Natural-language binding).

Skill: 1m-trade-dex (see skills/1m-trade-dex/SKILL.mdNatural-language binding and skills/1m-trade-dex/reference.md)

Wallet operations (synced with sub-skill docs):

StepWhereWhat
Create / manage walletBrowserhttps://www.1m-trade.com — official UI for account and wallet; do not recreate this flow in chat.
Bind CLI to the accountLocal shellhl1m init-wallet only — wallet public address + proxy (API) private key. Never use the main / master wallet private key.
VerifyAfter inithl1m query-user-state (and other hl1m query commands as needed).

Logic:

  1. Send users to https://www.1m-trade.com for wallet creation and ongoing management in the browser. Do not simulate full wallet creation inside the assistant.
  2. For CLI binding:
    • If the user provides both address and proxy key in one message (with labels such as wallet address and proxy private key, or other languages as mapped in 1m-trade-dex), follow 1m-trade-dex Natural-language binding: parse 0x + 40 hex (address) and 0x + 64 hex (proxy key), then run hl1m init-wallet --address <parsed> --pri_key <parsed> in a trusted shell; do not echo full keys in chat.
    • Otherwise, show the placeholder command only and ask the user to run locally:
    bash
    hl1m init-wallet --address 0xYourWalletAddress --pri_key 0xYourProxyPrivateKey
  3. After a successful init, use hl1m query-user-state to confirm the account is visible.

Workflow 3: Trading execution & management (Trading & Management)

Triggers: trade, order, open, close, positions, price, kline, HIP3, AAPL, GOLD

Skill: 1m-trade-dex

Logic:

  1. Market data: query kline/mids/meta as requested and format results.
  2. Pre-trade checks: ensure 1m-trade-dex is installed and run node auto_check.js to verify prerequisites. If it fails, do not execute any trades.
  3. Execution: follow the 1m-trade-dex documentation for the specific command.

Workflow 4: Hybrid orchestration (Hybrid Workflow)

Trigger examples: "check the market then decide whether to buy BTC", "after I init my wallet, show ETH kline"

Logic:

  1. Call Workflow 1 to fetch the market report.
  2. Present the report and ask whether to continue (e.g., "proceed to wallet setup or trading?").
  3. After confirmation, call Workflow 2 (wallet init guidance) or Workflow 3.

Examples

User: "How is the crypto market today? I also need to connect my Hyperliquid wallet." 1m-trade:

  1. Generate a market snapshot report (Workflow 1).
  2. Point to 1M-Trade for wallet creation/management as needed, then Workflow 2: if the user already sent labeled wallet address + proxy private key (or equivalent), parse and run hl1m init-wallet; otherwise give the placeholder command for local use (proxy key only; never the main wallet private key). Do not guide send-private-key.

User: "Search for the latest news about 'Bitcoin halving', then show BTC kline." 1m-trade:

  1. Call search (Workflow 1, Scenario 5) and return relevant items.
  2. Call kline query (Workflow 3) and return recent candles.

Workflow 5: Fully autonomous mode (AI Auto-Trader)

Triggers: enable auto trading, autonomous trading, managed, AI trade for me, run every N minutes, auto trade BTC

Logic:

  1. Run the checker once before enabling cron:

    • Repo root: node auto_check.js
    • If installed under the OpenClaw workspace: run node <skill_bundle_root>/auto_check.js If it fails, do not enable auto trading.
  2. Check whether the 1m-trade-auto-trader cron job exists:

    • Run openclaw cron list to verify whether it still exists.
    • If it exists, ask the user to stop/remove it before creating a new one.
    • If the user confirms it should be removed and it is still present, attempt to remove it with openclaw cron rm <task id>, then re-run openclaw cron list to confirm it is gone.
  3. Create a periodic workflow using the command below. --session isolated is fixed and must not be changed. The default interval is every 20 minutes (*/20); replace with */N if needed. Send the trading report to the user. Security constraints for the cron message:

    • Include ONLY the "#### Workflow content" block as the job prompt template.
    • Never include any secrets (API keys, private keys, passwords, .env contents, tokens).
    • Never include unrelated user/system text, terminal logs, or file contents.
    • Keep shell commands/placeholders unchanged, but you may translate natural-language instructions for locale.
  4. Run:

    bash
    openclaw cron add \
      --name "1m-trade-auto-trader" \
      --cron "*/20 * * * *" \
      --session isolated \
      --message "<Paste the FULL prompt from #### Workflow content through the end of the report template below; translate EVERY narrative line into the user's language (e.g. full Simplified Chinese if the user uses Chinese—no leftover English instructions). Keep skill names, hl1m subcommands, symbols, and <<...>> structure unchanged. No secrets. Each run outputs ONLY the final trading report; that report must be monolingual (all Chinese OR all English per user—no mixed prose). Replace this placeholder with that translated block.>" \
      --timeoutSeconds 600 \
      --announce \
      --channel <channel e.g. telegram> \
      --to "<user id>" \
Workflow content

Pre-start: dependency memory check All skills are installed locally.

  1. Try reading: $OPENCLAW_STATE_DIR/.1m-trade/dependencies-status.md

    • If missing → first run, treat as "not confirmed installed"
    • If present, look for any marker:
      • Installed: true
      • DependencyStatus: Installed
      • SkillsReady: true
    • Record status as "installed" or "not installed/unknown"
  2. Decide based on the status:

    • If clearly "installed" → skip checks/install and go to step 4
    • Otherwise → run step 3
  3. Only when initialization is needed: Ensure these skills are available in order:

    • 1m-trade-news
    • 1m-trade-dex If a skill is unavailable, attempt to install/enable it via the system's mechanism. Then record success in the memory file.
  4. Must execute: update/create the dependency memory file by overwriting:

# Dependency install marker - do not edit manually
Installed: true
Skills: 1m-trade-news (or others)
Skills Path: <skill paths>
LastChecked: 2026-03-15 14:30:00 UTC

Start execution

Start execution.

Workflow: Fully autonomous trading mode (AI Auto-Trader)

Execution Guidelines

  • Evaluate the full market universe (scan multiple assets). Trades are determined by risk controls; 0 to multiple trades are allowed.
  • Output must be a trading report only (no executable code). Markdown tables/quotes are allowed.
  • Do not create or modify any files.
  • Only call existing skills.
  • Use real trading (not simulation).

Response format

  • Your final assistant response must contain only the final trading report section in the required Markdown structure.
  • Language: The report must be fully in one language matching the user (see Locale / Monolingual output in #### 4. Trading brief) — no mixed Chinese/English prose.

Market universe (fixed; do not modify)

  • BTC
  • ETH
  • SOL
  • xyz:GOLD (alias: Gold)
  • xyz:CL (alias: Crude Oil)
  • xyz:SILVER (alias: Silver)
  • xyz:NVDA (alias: NVIDIA)
  • xyz:GOOGLE (alias: Google)
  • xyz:NATGAS (alias: Natural Gas)
  • xyz:BRENTOIL (alias: Brent Oil)
  • xyz:HOOD (alias: Robinhood) Quote currency: USDC

Execution loop: When triggered, execute the following steps in order. Avoid requesting intermediate confirmations; proceed with execution.

1. Intelligence & data collection (sense)
  • News: use 1m-trade-news to fetch the latest 20 newsflashes/news and determine whether they mention assets in the market universe to infer sentiment.
  • Kline: call 1m-trade-dexquery-kline (default 1h).
  • Wallet: call 1m-trade-dexquery-user-state.
  • Prices: call 1m-trade-dexquery-mids.
2. Decision

Decide based on news sentiment and kline trend:

  • Long
  • Short
  • Close
  • Hold

Mandatory risk controls & calculations:

  1. Each new position's notional value (after leverage) must be > 15 USDC (not balance).
  2. Calculate quantity rigorously using latest prices: qty (--qty) = target notional (USDC) / latest price, using appropriate precision.
3. Execution (act)

Based on the decision, use 1m-trade-dex commands to trade.

  • Example (market long/short): call market-order
  • Example (close): compute exact position size and place the appropriate market order
  • Example (limit): call place-order
  • If decision is Hold, do not execute any trade commands.
4. Trading brief (report)

Generate a brief report (not too long) describing the decision rationale and execution results. Follow this Markdown format strictly.

Locale: Infer the user’s primary language from the session (e.g. Chinese vs English). The report must be monolingualno zh/en mix in narrative text.

Language rule (strict):

  • Monolingual output (mandatory):
    • If the user’s language is Chinese (or they explicitly use Chinese): write the entire report in Chinese only — headings, bullets, table cells, and trading-status wording (e.g. use fully localized terms for hold / long / short / close, not English “Hold/Long/Short/Close” mixed into Chinese sentences).
    • If the user’s language is English: write the entire report in English only — no Chinese or other-language fragments in prose.
    • Allowed exceptions (do not “translate” these): canonical symbols and tickers (BTC, ETH, xyz:GOLD, …), the literal 1m-trade, pair suffixes like -USDC, numbers, and % where standard.
  • <<...>> are schema hints in this template only — strip them in the final answer. Do not print literal << or >> in the user-visible report. For each slot, output normal Markdown: localized headings and body text (e.g. - **Fundamentals**: weak market sentiment…), not - **<<Fundamentals>>**: … or • <<Fundamentals>>: …. The reader must see finished prose, not bracket markers.
  • Translate/replace the meaning of each former <<...>> slot into the user’s language (including example values that stood in for real content).
  • Do NOT translate placeholders inside <...>.
  • Do NOT translate crypto symbols, tickers, or trading pairs (e.g. BTC, ETH, SOL, xyz:GOLD). Keep them exactly as-is.
  • Do NOT translate the literal string 1m-trade anywhere.
  • Asset display name rule:
    • If the asset has an alias in the Market universe list, use the alias as the display name (alias text should follow the translation rule). Do NOT display the canonical symbol.
    • If the asset has no alias, use the canonical symbol as-is.

🤖 1m-trade <<AUTONOMOUS_TRADING_REPORT>>: <<ACCOUNT_BALANCE>>: <> <>: Table coverage (same idea as per-asset section): If the market universe is large, do not fill one row per symbol by default. Prefer: (a) a narrow table — only rows for assets with material activity this run (traded, opened/closed, non-Hold, or materially different), plus one summary line for “everything else” (e.g. all others: Hold / no action); or (b) a short bullet summary instead of a wide table. When the set is small, you may use the full table pattern below.

<><<LATEST_PRICE>><<TREND_TIMEFRAME>><><>
BTCxxx<><><>
ETHxxx<><><<Opened long 0.012 ETH>>
<>xxx<><><>
...............

🧠 <<PER_ASSET_DECISIONS>>

Coverage rule: If the market universe is large or a full per-asset write-up would make the report too long, prefer a summary instead of repeating the block below for every symbol. In summary mode: give one cross-asset fundamentals/sentiment paragraph, portfolio-level account state, then short bullets only for assets that mattered (e.g. traded this run, non-Hold decision, material risk, or materially different from the rest). End with a brief execution recap. Strip <<...>> in final output; stay monolingual.

When the set is small (or the user asked for full detail), repeat per asset:

[ASSET]-USDC

  • <>: <<top relevant news / sentiment summary>>
  • <<ACCOUNT_STATE>>: <<none / long X / short X>>
  • <<DECISION_RATIONALE>>: <<fundamentals + technicals>> → <<Long/Short/Hold/Close>>
  • <>: <<✅ executed (or ⏸️ hold, no action)>>

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the 1m Trade AI skill do?

Integrated on-chain operations hub: integrates BlockBeats market intelligence, Hyperliquid DEX trading via `hl1m`, wallet creation and management at https://www.1m-trade.com, and supports local initialization using `hl1m init-wallet` (wallet address + proxy private key, never use the main wallet private key). Supports fully autonomous AI trading.

Why use 1m Trade on TypingMind?

Because you install it once and use it with any model. 1m Trade is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 1m Trade in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/1m-trade. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 1m Trade?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 1m Trade?

As many as you like. As long as a model supports skills, you can use 1m Trade with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 1m Trade AI skill free?

Yes. It is published on GitHub by LeoYeAI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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