SKILLEMALL.ai

AC task-ops

四模块价值链任务操作系统。包含:1) Domain Elimination Assessor(领域消除评估)——评估领域存在必要性;2) Workflow Refactor(工作流重构)——重构复杂工作流为IPO基元链;3) Domain Payload Generator(领域负载物生成)——将领域知识结构化为技能文件;4) Universal Task OS(通用三轴任务操作系统)——执行轴+内容轴+创新轴。形成评估→转化→创建→执行的完整价值链。触发词:三轴、执行、内容、创新、任务系统、管线、Pipeline、工作流重构、流程重构、领域负载物、领域技能生成、领域消除、领域评估、任务编排、能力单元、IPO基元、元操作、清单法、样本法、创新模式、创新元框架、领域负载物技能、知识参考库、任务分解。

ClawHub Agent Skills author: 波动几何 v1.0.3 MIT-0 13 files body ≈ 1 051 tokens Open the sourceclawhub.ai analyzed 13 h ago

四模块价值链任务操作系统。包含:1) Domain Elimination Assessor(领域消除评估)——评估领域存在必要性;2) Workflow Refactor(工作流重构)——重构复杂工作流为IPO基元链;3) Domain Payload…

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
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
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: 13. 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. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1051 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 353: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (11 of 11)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
This is a coherent task-workflow skill, but it can activate very broadly and direct agents to create or save new skills and use tools without clear user-confirmation boundaries.
LLM: suspicious (high) · VirusTotal: · 16 Jun 2026