SKILLEMALL.ai

BC baozong-trading

宝总霸盘Skill — A股/港股/美股全市场智能操盘系统。当用户提到以下任何场景时激活: 股票分析、个股诊断、持仓检查、盘前机会、每日复盘、选股、技术面、基本面、 政策影响、监管动态、研报解读、估值分析、买卖决策、风控检查、回测策略、 量化策略、自选股监控、异动预警、市场情绪、板块轮动、龙虎榜、主力动向、 北向资金、融资融券、财报分析、估值、止损、止盈、仓位管理、股池维护。 关键词:炒股、买股、卖股、持仓、盯盘、操盘、选股、复盘、股票诊断、个股分析、 市场分析、龙头战法、价值投资、趋势交易、量化、backtest、回测、风控、止损。

ClawHub Agent Skills author: mingyuan v1.0.0 MIT-0 2 files body ≈ 1 060 tokens Open the sourceclawhub.ai analyzed 4 d ago

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

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
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: 2. 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. 74 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1060 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
  • -223 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 270: enough signal without eating the budget
  • +4Structure: 23 headings
  • +3Step-by-step instructions: 74 items
  • +4Has examples (7 code blocks)

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

External checks

ClawHub: clean
This is a disclosed, instruction-only stock analysis skill with broad finance triggers, but it does not install code, access accounts, place trades, or hide behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026