SKILLEMALL.ai

AD zeyang-strategy-lab-free

用于本地单标的历史数据研究与策略验证,支持 EMA、SMA 或 RSI 的做多/空仓规则,并生成基础 JSON、CSV、Markdown 与图表文件。仅用于历史研究与教育,不用于实盘交易或投资建议。 Run local single-asset historical research with EMA, SMA, or RSI long/cash rules and produce basic JSON, CSV, Markdown, and chart artifacts. Use for research and education, not live trading or investment advice.

ClawHub Agent Skills author: ZeYang v0.1.0 MIT-0 20 files body ≈ 803 tokens Open the sourceclawhub.ai analyzed 2 d ago

用于本地单标的历史数据研究与策略验证,支持 EMA、SMA 或 RSI 的做多/空仓规则,并生成基础 JSON、CSV、Markdown 与图表文件。仅用于历史研究与教育,不用于实盘交易或投资建议。 Run local single-asset historical research with EMA, SMA…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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 · 0

    ✓ No critical or high findings

    Files scanned: 16. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 46/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (zeyang-strategy-lab-free) differs from the folder (zeyang-strategy-lab)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 6 steps
    • 100Execution cost. Instruction body is 803 tokens
    • 100Running it twice. No mutating operations

    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
    • -35 of 6 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 311: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 6 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (2 of 4)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: clean
    This is a local research backtesting skill that reads user-provided CSV files and writes local result artifacts, with no evidence of credential access, networking, persistence, or live trading.
    LLM: benign (high) · VirusTotal: · 11 Sept 2026