BC 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.
Autonomous Hyperliquid trading agent powered by smart money signals.
As a process C 61/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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-tokenreferences/schema.md:224High-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-longSKILL.md body ≈ 5050 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 61/100
- 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
- 85Steps. 93 steps, 2 vague phrases
- 100Failures and branches. 5 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.
In the sandbox Скрипты не запустились
The skill's scripts were run in a throwaway machine: no network, fake keys in the home directory, a tracer watching. We wrote down what they did. Reaching for the network or for secrets caps the technical grade at C; a quiet run adds no points.
Запущено 1 скрипт; каждому дали двадцать секунд, поддельный домашний каталог с ключами и сеть, в которой ничего нет.
Ни один не дошёл до работы — им не хватило зависимостей, аргументов или файлов. Это не отзыв о поведении: наблюдать было не за чем.
scripts/zonein.py | не запустился: -h, --help show this help message and exit |
29 Oct 2026