SKILLEMALL.ai

BC workflow-refactor

工作流重构方法。核心能力:将任何领域的复杂工作流重构为AI辅助一人简易完成的方法(拆解人的局限补偿层→消除→基于AI能力模型重整)。三步法:拆解(识别每个环节的存在理由)→消除(去掉人的局限补偿层)→重整(基于AI能力模型重编为端到端IPO基元链)。覆盖从传统工作流识别、环节分析、补偿层消除、IPO基元链重整、重构验证到执行形态选择的全流程。6种任务类型、每种任务的组件清单与1个完整实战范本。通用方法,不绑定任何特定领域。触发词:工作流重构、流程重构、流程简化、workflow refactor、工作流优化、流程再造、流程重组、消除冗余环节、端到端重构。

ClawHub Agent Skills author: 波动几何 v1.0.2 MIT-0 2 files body ≈ 2 199 tokens Open the sourceclawhub.ai analyzed 2 d ago

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

ProcedureSoftware developmentInfrastructuretype 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. 46 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2199 tokens
  • 100Running it twice. No mutating operations
  • low 12 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
  • -239 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 280: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 46 items
  • +4Has examples (2 code blocks)

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

External checks

ClawHub: clean
This appears to be a workflow/process-refactoring guidance skill with broad activation wording but no evidence of code execution, credential access, persistence, or hidden data handling.
LLM: benign (medium) · VirusTotal: · 28 May 2026