SKILLEMALL.ai

AC shisoleaf-alpha

紫苏叶瓶颈投资策略——不追明星龙头,专挖产业链第五层"紫苏叶"(全球仅1-2家寡头、缺了整条链停摆的上游冷门标的)。蒸馏自X平台传奇"白毛股神"Serenity(公开标的胜率86%、中位收益63%),融合紫苏叶理论、瓶颈逆向拆解、碎片信息拼图三大武器。Use when: bottleneck hunting, supply chain chokepoint analysis, upstream monopoly finding, 产业链瓶颈分析, 卡脖子标的挖掘, 逆向拆解产业链, 冷门上游客头扫描, ShisoLeaf strategy, purple leaf theory.

ClawHub Agent Skills author: lingfeng-19 v1.0.0 MIT-0 2 files body ≈ 724 tokens Open the sourceclawhub.ai analyzed 2 d ago

紫苏叶瓶颈投资策略——不追明星龙头,专挖产业链第五层"紫苏叶"(全球仅1-2家寡头、缺了整条链停摆的上游冷门标的)。蒸馏自X平台传奇"白毛股神"Serenity(公开标的胜率86%、中位收益63%),融合紫苏叶理论、瓶颈逆向拆解、碎片信息拼图三大武器。Use when: bottleneck hunting…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerGitHubAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 3, column 14: description: 紫苏叶瓶颈投资策略——不追明星龙头,专挖产业链第五层"紫苏叶"(全球仅1-2家寡头、缺了整条链停摆的上游冷门标的)。蒸馏自X平台传奇… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value

    Process rating: all ten parameters 53/100

    • 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
    • 100Tools and files. No external tools needed
    • 100Steps. 18 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 724 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
    • +2Single-language instructions
    • +3Description length 293: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 18 items
    • +4Has examples (2 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

    External checks

    ClawHub: clean
    This is a disclosed investment-research methodology skill with no executable code, persistence, credential use, or hidden data access.
    LLM: benign (high) · VirusTotal: · 9 Aug 2026