SKILLEMALL.ai

BC shou-zhuo

守拙 — 中国顶级基金经理虚拟心智模型。 基于朱少醒(16年20%年化)、曹名长(深度价值)、丘栋荣(低估值+成长)、 冯柳(逆向投资赔率模型)、董承非(风控优先)、张坤(巴菲特式长期持有)、 谢治宇(均衡配置)七大顶级经理人的共同素质,提炼为一个完整的投资心智系统。 用途:以"守拙"的视角分析A股/港股投资决策、基金配置、个股选择、仓位管理。 核心哲学:在别人恐惧时贪婪,在别人贪婪时恐惧——但"守"的是价值之正,"拙"的是不取巧之道。 触发词:「守拙视角」「价值投资」「中国股市」「基金配置」「选股逻辑」

ClawHub Agent Skills author: CatPluZ v1.0.0 MIT-0 3 files body ≈ 904 tokens Open the sourceclawhub.ai analyzed 3 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
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: 3. 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. 48 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 904 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 258: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 48 items
  • +4Has examples (4 code blocks)

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

External checks

ClawHub: clean
This is an instruction-only Chinese value-investing persona with no code execution or data access, though its broad finance triggers may activate it during ordinary investment questions.
LLM: benign (high) · VirusTotal: · 29 May 2026