SKILLEMALL.ai
GitHub ↗ RU Sign in

AC hyperliquid-trading-agent

Autonomous Hyperliquid trading agent powered by smart money signals. Create, backtest, and deploy AI trading agents that track 500+ whale wallets on Hyperliquid — perps, spot, and HIP-3 assets (TSLA, NVDA, GOLD, US500). Multi-timeframe technical analysis, derivatives flow, funding rates, liquidation maps, and a self-learning execution engine. HITL trade plans via Telegram. Also supports Polymarket prediction markets. 30+ commands, one API key.

ClawHub Agent Skills author: Phu Trinh v2.3.8 MIT-0 11 files body ≈ 5 050 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice

IntegrationTelegramAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
99
Quality 40%
83
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Running it twice w 4
30
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token references/schema.md:224
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "withdrawal_addresses": ["0x59…1Dd"],
    quoted

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5050 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 63/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 33 mutating operations with no state check
  • 40Consistency. Frontmatter name (hyperliquid-trading-agent) differs from the folder (zonein)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5050 tokens
  • 100Steps. 93 steps
  • 100Failures and branches. 7 branches, has a failure section
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 447: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 93 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (7 of 7)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

External checks

ClawHub: suspicious
This is a disclosed trading-agent skill, but it can control real-money automated trading and has under-guarded state changes and secret-handling gaps that should be reviewed before installation.
LLM: suspicious (high) · VirusTotal: · 28 May 2026