SKILLEMALL.ai

BC institutional-speculative-capital-convergence

牛股王独家研发的A股机游共振选股模型,基于机构资金与游资动向双重筛选,精准定位同时被机构和游资关注的股票,这类股票兼具基本面支撑和短线活跃度。提供三大优选策略——主线擒龙、波段潜伏、小盘绩优,覆盖短线热点、中期波段、成长黑马多种交易风格,帮助投资者快速锁定市场中长短资金共同认可的标的。

ClawHub Agent Skills author: maomaoxx779-cmd v1.0.0 MIT-0 4 files body ≈ 829 tokens Open the sourceclawhub.ai analyzed 4 d ago

牛股王独家研发的A股机游共振选股模型,基于机构资金与游资动向双重筛选,精准定位同时被机构和游资关注的股票,这类股票兼具基本面支撑和短线活跃度。提供三大优选策略——主线擒龙、波段潜伏、小盘绩优,覆盖短线热点、中期波段、成长黑马多种交易风格,帮助投资者快速锁定市场中长短资金共同认可的标的。

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

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

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 829 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 143: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill is a stock-screening helper, but it includes a hardcoded usertoken despite saying no API key is needed.
LLM: suspicious (high) · VirusTotal: · 30 Jul 2026