SKILLEMALL.ai

AD shiwei-diagnosis

施炜企业管理诊断方法论。基于PRACDOM实践智慧管理研究院的诊断体系(巴奴、沃森生物、法兰泰克三份完整报告提炼)。 以"企业成长五阶段模型"和"一心开二门"为理论基石,以"资料+访谈+问卷"三角验证为调研手段, 以"成功经验回顾→问题三层递进诊断→变革方向建议"为报告骨架,以战略/运营/组织/人才/文化/领导/财务七大维度为分析框架, 运用"赢的逻辑"七维成功要素分析、企业家素质模型(四力/四有)、战略飞轮等工具完成系统性管理诊断。 输出结构化的诊断MD文档,并可参照模板生成诊断PPT。 适用场景:企业管理咨询诊断、组织能力评估、企业成长阶段判断、战略与组织问题分析、 变革方向建议。触发词:管理诊断、企业诊断、组织诊断、施炜诊断、管理咨询诊断、 PRACDOM、企业问题分析、组织能力评估。

ClawHub Agent Skills author: tuobadaidai v1.1.0 MIT-0 7 files body ≈ 1 216 tokens Open the sourceclawhub.ai analyzed 3 d ago

施炜企业管理诊断方法论。基于PRACDOM实践智慧管理研究院的诊断体系(巴奴、沃森生物、法兰泰克三份完整报告提炼)。 以"企业成长五阶段模型"和"一心开二门"为理论基石,以"资料+访谈+问卷"三角验证为调研手段,…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 7. 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 46/100

  • 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
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 42 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1216 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

  • +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
  • +5Description quotes 3 example trigger phrases
  • +3Description length 350: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

External checks

ClawHub: suspicious
The skill is mostly a disclosed business-diagnosis and PPT workflow, but its bundled scripts include unsafe local command execution and a hard-coded client-specific PPT output path.
LLM: suspicious (high) · 24 Jun 2026