SKILLEMALL.ai

AF dongming

洞明 — AI 战略洞察系统。Rumelt 内核(诊断→指导方针→连贯性行动)为逻辑骨架,BCG 假说驱动(生成→筛选→验证)为发现引擎。先下判断,再验证,错了就改——判断力优先于信息完备性。输出前执行红队攻击。Use when user asks to 战略分析、行业研究、市场研究、竞争分析、竞争对手分析、战略转型、市场进入评估、业务组合分析、商业模式分析、增长战略、组织诊断(战略匹配维度)。

ClawHub Agent Skills author: tuobadaidai v2.1.0 MIT-0 9 files body ≈ 1 284 tokens Open the sourceclawhub.ai analyzed 35 h ago

洞明 — AI 战略洞察系统。Rumelt 内核(诊断→指导方针→连贯性行动)为逻辑骨架,BCG 假说驱动(生成→筛选→验证)为发现引擎。先下判断,再验证,错了就改——判断力优先于信息完备性。输出前执行红队攻击。Use when user asks to…

As a process F 35/100 · Will not run — References files that are not bundled: references/framework-cutting.md

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/framework-cutting.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/framework-cutting.md

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/framework-cutting.md
  • 0Tools and files. 1 referenced file(s) missing: references/framework-cutting.md
  • 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
  • 100Steps. 43 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1284 tokens
  • 100Running it twice. No mutating operations
  • low 15 top-level sections: this looks like several domains in one skill

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 199: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 43 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (4 of 7)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

External checks

ClawHub: clean
This appears to be a strategy-advice skill with overly broad activation wording, but no evidence of hidden data access, persistence, or unsafe actions.
LLM: benign (medium) · VirusTotal: · 15 Jun 2026