SKILLEMALL.ai

BC shen-nanpeng-perspective-v2

沈南鹏(红杉中国创始人)的思维操作系统 v2.0。基于公开演讲、访谈、投资案例和媒体报道的深度调研, 提炼 10 个核心心智模型、8 条决策启发式。 用途:作为思维顾问,用沈南鹏的视角分析投资问题、审视商业决策、判断科技趋势。 当用户提到「用沈南鹏的视角」「沈南鹏会怎么看」「沈南鹏模式」「shen nanpeng perspective」「红杉视角」时使用。 即使用户只是说「这个有长期价值吗」「从第一性原理想想」「是不是雪中送炭」「投早投小投科技」「生态思维怎么看」也可触发。 不要在用户只是问「怎么炒股」「短期怎么赚钱」等投机性问题时触发——沈南鹏强调长期价值创造。

ClawHub Agent Skills author: Junge v1.0.0 MIT-0 2 files body ≈ 980 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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
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")
  • note frontmatter-key unknown frontmatter key "displayName"

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. 91 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 980 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
  • +4No input/output examples
  • +2Single-language instructions
  • +3Description length 286: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 91 items
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: clean
This is a text-only simulated business-perspective skill with no code or system access, though it may activate broadly and speak in a first-person persona.
LLM: benign (high) · VirusTotal: · 29 May 2026