BC crypto-drt-scalping
Crypto DRT scalping — Dealing Range Theory on 12 crypto pairs (TRX, BNB, BTC, LINK, AVAX, DOGE, SOL, NEAR, XRP, LDO, ADA, ETH), all 7 days. Backtested 2 years (~400+ trades). Backtest results are historical and not a guarantee of future performance. Separate play-money account rules.
Crypto DRT scalping — Dealing Range Theory on 12 crypto pairs (TRX, BNB, BTC, LINK, AVAX, DOGE, SOL, NEAR, XRP, LDO, ADA, ETH), all 7 days.
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:114High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- **Payment**: USDC on Ethereum to `0xaf…CF8`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:131High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- **Payment**: USDC on Ethereum to `0xaf…CF8`
quoted
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 51/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 43 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1304 tokens
- low 13 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
- -212 emoji in the instructions: noise for the model
- -31 of 2 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 284: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 43 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.