CC grid-trading
Dynamic grid trading strategy for any token pair on EVM L2 chains via OKX DEX API. Features asymmetric grid steps (buy-dense/sell-wide in bullish, reverse in bearish), multi-timeframe trend analysis, trend-adaptive grid sizing, ATR-based volatility, sell trailing optimization, and HODL Alpha tracking. Covers grid modes (arithmetic/geometric), asymmetric buy/sell grid spacing, position sizing strategies (equal/martingale/anti-martingale/pyramid/trend-adaptive), comprehensive risk controls (stop-loss, take-profit, drawdown protection, circuit breakers), trade execution via OKX DEX aggregator, PnL calculation, and Discord notification. Use when creating, modifying, debugging, or tuning a grid trading bot.
Dynamic grid trading strategy for any token pair on EVM L2 chains via OKX DEX API.
As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 2
✓ No critical or high findings
Medium and low: 2
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low Exfiltration
read-dotenvREADME.md:84Reads a .env filecp ../.env.example .env # 填入 API keys + 钱包地址
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low Exfiltration
exfil-webhook-urlreferences/eth_grid.py:1233Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)url = f"https://api.telegram.org/bot{TELEGRAM_BOT_TOKEN}/sendMessage"placeholder
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 7391 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70Execution cost. Instruction body is 7391 tokens
- 85Steps. 79 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- low 17 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)
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +3Description length 711: enough signal without eating the budget
- +4Structure: 45 headings
- +3Step-by-step instructions: 79 items
- +4Has examples (22 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.