AC okx-quant-trade
Comprehensive quantitative trading skill for OKX. Use when user asks to 'analyze market', 'calculate RSI', 'check EMA', 'compute bollinger bands', 'buy BTC', 'sell ETH', 'place order', 'long perp', 'short swap', 'set stop loss', 'set take profit', 'check positions', 'cancel order', 'set leverage', 'trailing stop', or any quantitative analysis + order execution task on OKX. Combines Python-based technical indicator computation (RSI, EMA 5/10/20, Bias, Bollinger Bands) with OKX CLI for actual order placement. Requires API credentials for trading operations. Do NOT use for grid/DCA bots (use okx-cex-bot).
As a process C 61/100 · Has gaps — weak spots: result and completion, progress reporting
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 · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5465 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 61/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 5465 tokens
- 100Steps. 74 steps
- 100Consistency. Name and required fields are in place
- 100Running it twice. No mutating operations
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (6 tags): a typed call is more reliable
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
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 609: enough signal without eating the budget
- +4Structure: 49 headings
- +3Step-by-step instructions: 74 items
- +4Has examples (33 code blocks)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.