Apex Strategy logo

Apex Strategy

Organization
Nunchi-trade
apex-strategy

Autonomous multi-slot trading orchestrator

Overview

PublisherNunchi-trade
Repositoryagent-cli
Skill nameapex-strategy
Stars
521
Forks
136
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by Nunchi-trade on GitHub. Read the source before you install it.

Installation

Install the Apex Strategy 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.
    https://github.com/Nunchi-trade/agent-cli/tree/main/skills/apex
  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/Nunchi-trade/agent-cli.git /tmp/agent-cli
mkdir -p .claude/skills
cp -r /tmp/agent-cli/skills/apex .claude/skills/apex-strategy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Apex Strategy 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 Apex Strategy 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 Apex Strategy 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.

APEX Strategy

Autonomous multi-slot trading strategy that composes Radar + Pulse + DSL into a unified orchestrator.

Architecture

APEX runs a single tick loop (60s base) that:

  1. Every tick: Fetch prices, update ROEs, check DSL guards, run pulse, evaluate entry/exit
  2. Every 5 ticks (5 min): Watchdog health check (verify positions match exchange)
  3. Every 15 ticks (15 min): Run opportunity radar, queue high-score setups

Slot Management

  • 2-3 concurrent positions (configurable)
  • Each slot: EMPTY -> ACTIVE -> CLOSED (reset to EMPTY)
  • No duplicate instruments across slots
  • Max 2 same-direction positions

Entry Priority

  1. Pulse IMMEDIATE_MOVER -> auto-enter
  2. Radar score > 170 -> queue entry
  3. Pulse other signals (confidence > 70) -> enter

Exit Priority

  1. DSL trailing stop CLOSE
  2. Hard stop: ROE < -5%
  3. Conviction collapse: signal gone + negative PnL for 30+ min
  4. Stagnation: ROE stuck above 3% for 60+ min

Risk Management

  • Per-slot margin: total_budget / max_slots
  • Daily loss limit: $500 (default)
  • Daily loss trigger: close all positions immediately

Prerequisites

Before running APEX live (not mock), ensure:

  1. Testnet: Claim USDyP first — hl setup claim-usdyp (without funds, all orders fail silently)
  2. Mainnet: Deposit USDC via the Hyperliquid web UI
  3. Builder fee: Approve once per network — hl builder approve (testnet) or hl builder approve --mainnet

Usage

bash
# Mock mode (no funds needed)
hl apex run --mock --max-ticks 10

# Live (testnet) — requires USDyP balance + builder approval
hl apex run

# Live (mainnet) — requires USDC balance + mainnet builder approval
hl apex run --mainnet

# Check status
hl apex status

# List presets
hl apex presets

Presets

  • default: 3 slots, 10x leverage, $10K budget
  • conservative: 2 slots, 5x leverage, higher thresholds
  • aggressive: 3 slots, 15x leverage, lower thresholds

Agent Mandate

You are the APEX orchestrator. Your job is to hunt for high-probability setups and manage 2-3 concurrent positions with strict risk controls.

RULES:

  • NEVER exceed max_slots concurrent positions
  • ALWAYS check daily_loss_limit before entering new positions
  • NEVER enter a position without Radar score > 170 OR Pulse IMMEDIATE signal
  • ALWAYS run DSL trailing stop on every active position
  • Exit ALL positions immediately if daily loss exceeds limit
  • ALWAYS run --mock --max-ticks 5 before first live deployment
  • Log every entry/exit decision with reasoning

Decision Rules

ConditionAction
Radar score > 200 + Pulse IMMEDIATEEnter with 1.5x size — strongest conviction
Radar score > 170, no Pulse signalEnter with 1.0x size — radar-only conviction
Radar score 140-170Queue entry, wait for Pulse confirmation within 15 min
Radar score < 140Skip — insufficient edge
ROE > 5% and DSL Phase 2 activeLet DSL manage exit — do not manually close
ROE < -3% for > 15 minExit — conviction lost, don't wait for hard stop
2 consecutive losses same sessionReduce position size by 50% for next 2 trades
Daily loss > 50% of limitSwitch to conservative preset for remainder
All slots filledWait for exit before scanning new entries
Pulse IMMEDIATE but all slots fullEvaluate weakest slot for replacement

Anti-Patterns

  • Over-leveraging on volatile days: Using aggressive preset during high-VIX or post-CPI → blown account. Use conservative preset on macro days.
  • "One more trade to recover": After hitting daily loss limit, entering another trade always makes it worse. Hard stop means hard stop.
  • Chasing Pulse signals alone: Entering on VOLUME_SURGE without Radar confirmation → 60% historical loss rate. IMMEDIATE_MOVER is the only standalone entry signal.
  • Tight stops on entry: DSL Phase 1 exists to give the trade room. Overriding with tight custom stops → premature exits on noise.
  • Running without budget cap: Always set --budget. Unbounded budget = unbounded loss.

Error Recovery

ErrorCauseFix
No positions but slots show ACTIVEStale state after restarthl apex status, manually reset via state file
Radar returned 0 candidatesLow-vol period or API issueNormal during weekends/low-vol — APEX will idle safely
Daily loss limit reachedBad sessionAPEX auto-closes all. Review with hl reflect run tomorrow
Builder fee not approvedSkipped onboarding stephl builder approve then restart APEX
Connection timeoutHL API rate limitAPEX auto-retries with backoff — no action needed

Composition

APEX is the top-level orchestrator. It composes Radar (opportunity finding), Pulse (real-time signal detection), and DSL (risk management) into one tick loop. Use APEX for autonomous trading. Use individual skills when you need manual control.

Cron Template

bash
# Start APEX at market open, stop at EOD
0 8 * * 1-5  cd ~/agent-cli && source .venv/bin/activate && hl apex run --budget 5000 >> logs/apex.log 2>&1
0 20 * * 1-5 pkill -f "hl apex run"
# Nightly REFLECT review
55 23 * * * cd ~/agent-cli && source .venv/bin/activate && hl reflect run >> logs/reflect.log 2>&1

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 Apex Strategy AI skill do?

Autonomous multi-slot trading orchestrator

Why use Apex Strategy on TypingMind?

Because you install it once and use it with any model. Apex Strategy 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 Apex Strategy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Nunchi-trade/agent-cli/tree/main/skills/apex. 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 Apex Strategy?

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 Apex Strategy?

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

Is the Apex Strategy AI skill free?

Yes. It is published on GitHub by Nunchi-trade 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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