opportunity-radar

A market-screening workflow for finding trading setups among Hyperliquid perpetual markets. Perpetual markets are contracts that track an asset's price without a fixed expiry date.

In plain words
What is it for?
Use it for one-time or repeated scans of Hyperliquid markets, with optional JSON output or mock data when no live connection is available.
Why use it?
It narrows many markets using liquidity, price trends, momentum, open interest, volume, funding costs, and Bitcoin market conditions. It also removes setups that fail its stated risk filters.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/nunchi-trade/agent-cli/radar
Any agent
npx skills add Nunchi-trade/agent-cli --skill radar
Clone the repo
git clone --depth 1 https://github.com/Nunchi-trade/agent-cli

Made for: Claude Code, Codex.

Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,199 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00017 $0.01199
Opus 5 $0.00009 $0.00600
Sonnet 5 $0.00003 $0.00240
Haiku 4.5 $0.00002 $0.00120

Measured 3d ago against content hash d8ca2a2b15cc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

opportunity-radar scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/standalone_runner.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/radar/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Opportunity Radar

Screens all Hyperliquid perpetual markets through a 4-stage funnel to surface the highest-conviction trading setups.

Architecture

Stage 0: BTC Macro Context (EMA 5/13 on 4h, 1h momentum)
Stage 1: Bulk Screen (~500 assets → ~70 by volume)
Stage 2: Top-N Selection (by composite liquidity score)
Stage 3: Deep Dive (multi-TF technicals + 3-pillar scoring)
Stage 4: Momentum + Final Ranking

3-Pillar Scoring (0-400 scale)

Pillar Weight Signals
Market Structure 35% Volume tiers, surge, OI, OI/Vol health
Technicals 40% 4h trend, hourly trend, RSI, patterns, volume
Funding 25% Neutral (+40), favorable, unfavorable penalties

Hard Disqualifiers

  1. Counter-trend on hourly structure
  2. Extreme RSI (>80 for LONG, <20 for SHORT)
  3. Strong 4h counter-trend (strength > 50)
  4. Volume dying on both timeframes
  5. Heavy unfavorable funding (>50% annualized)
  6. BTC macro headwind (modifier < -30)

Usage

CLI

hl radar once              # Single scan
hl radar run --tick 900    # Continuous (15 min intervals)
hl radar once --json       # JSON output
hl radar once --mock       # With mock data (no HL connection)
hl radar status            # Show last scan results
hl radar presets            # List presets

Standalone

from skills.radar.scripts.standalone_runner import RadarRunner
from cli.hl_adapter import DirectHLProxy

runner = RadarRunner(hl=hl, tick_interval=900)
runner.run()

Configuration

Via YAML config or CLI flags:

  • --min-volume: Minimum 24h volume to qualify (default: $500K)
  • --top-n: Assets to deep dive (default: 20)
  • --preset: "default" or "aggressive"
  • --score-threshold: Minimum final score (default: 150)

Agent Mandate

You are the opportunity radar. Your job is to screen the entire Hyperliquid perps universe and rank assets by trading conviction. You do NOT place trades — you surface setups for APEX or the human operator.

Read the full file on GitHub · 124 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 124 lines · 17 tokens per session scan A d8ca2a2b15cc

Subscribe to this mod's changes

opportunity-radar is a skill published in the GitHub repository Nunchi-trade/agent-cli (515 stars, last pushed 1mo ago), licensed MIT. It adds 17 tokens to every session and 1,199 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

opportunity-radar

Screens all Hyperliquid perps and surfaces top trading setups.

clawd-aftermath/nunchi-for-aftermath · 17 tokens

hyperliquid

Use when backtesting, deploying, funding, or debugging a live trading strategy on Hyperliquid through the Superior Trade API — writing Freqtrade configs and strategy code, running backtest sweeps, checking wallet balances, depositing USDC, trading HIP-3 stock/commodity perps, or diagnosing a deployment that will not…

Superior-Trade/superior-skills · 73 tokens

polymarket

Use when the user wants to trade, research, or backtest Polymarket prediction markets through Superior Trade — finding markets by slug or event URL, placing a single immediate market order, writing NautilusTrader strategies, running filled-data backtests, funding pUSD, or deploying and monitoring a live Polymarket…

Superior-Trade/superior-skills · 68 tokens

backtesting

Use when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps, walk-forward validation, zero-trade diagnosis, compute-cost estimation, or "is this backtest result trustworthy?". Pair with the relevant strategy…

Superior-Trade/superior-skills · 73 tokens

basis-arb

Use when the user asks for spot-perp basis trade, basis arbitrage, cash-and-carry, perp discount, or any setup that reads the spot–perp basis as a positioning signal. Long-perp leg only — pure two-leg basis arb requires a paired spot short (or long) which Freqtrade can't run cleanly. The strategy below captures the…

Superior-Trade/superior-skills · 87 tokens

fees-optimizations

Use when the user asks about fees, fee optimization, slippage, maker vs taker, post-only or ALO orders, fee tiers, builder code fees, effective spread, order pricing, lowering trading costs, or why a live Hyperliquid Freqtrade strategy underperforms its backtest. Also use proactively for high-turnover designs (5m or…

Superior-Trade/superior-skills · 94 tokens