SKILLEMALL.ai

AD yotta-humanize

元真 —— 去 AI 味的中文写作编辑技能:检测器引擎(24 类规则 + 词表 + 统计突发性)识别并改写 AI 腔文本,让中文写作更自然、更像人写的。触发:编辑 / 润色文本、去 AI 味、让文章 / 文案 / 回复更像人写、发现文本充斥着 AI 常用词与句式(赋能 / 闭环 / 值得注意的是 / 综上所述 / 希望对你有所帮助 等)、给 AI 生成的中文稿件做检测与改写。边界:只处理文本,不生成新内容;不改写事实 / 数据 / 专有名词;不破坏作者原意;改写为确定性规则,不依赖模型。

ClawHub Agent Skills author: YottaMeta v0.2.0 MIT-0 18 files · 1 script body ≈ 576 tokens Open the sourceclawhub.ai analyzed 2 d ago

元真 —— 去 AI 味的中文写作编辑技能:检测器引擎(24 类规则 + 词表 + 统计突发性)识别并改写 AI 腔文本,让中文写作更自然、更像人写的。触发:编辑 / 润色文本、去 AI 味、让文章 / 文案 / 回复更像人写、发现文本充斥着 AI 常用词与句式(赋能 / 闭环 / 值得注意的是 / 综上所述 /…

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
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: 17. 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 (python) that frontmatter does not declare
  • 100Steps. 21 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 576 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
  • -32 of 3 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 246: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This skill is a local Chinese text-editing helper with disclosed installers, though its shell installer needs care with custom destinations.
LLM: benign (high) · VirusTotal: · 9 Sept 2026