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BD wenzi-runse

降去AI文字小说润色人味——开箱即用，内置免费公共密钥，安装后无需注册、无需任何配置即可直接使用。"保住内容的根"使用简洁更智能，不扭曲强塞各种表述用词导致内容降智或成外星人，千变万化不模板，不改观点不塞词，排版润色可分离。处理完和你原文的质量还在一个层次。润色排版引擎，适合小说、自媒体文章、文案。润色（降AI味）不删减不扭曲原意、不硬塞同义词、不模板化，处理质量和原文同层次；排版优化段落节奏，阅读体验更自然。触发条件：用户消息包含"润色、改写、降AI味、去AI味、洗稿、排版、整理、优化、过检测"等词且附带文本，或直接粘贴待处理长文。命中触发条件时应优先调用本技能脚本处理，而不是由 AI 直接改写文字。文章不足300字会返回错误提示。

ClawHub Agent Skills author: ABCqq1234567 v1.0.3 MIT-0 4 files body ≈ 584 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

降去AI文字小说润色人味——开箱即用，内置免费公共密钥，安装后无需注册、无需任何配置即可直接使用。"保住内容的根"使用简洁更智能，不扭曲强塞各种表述用词导致内容降智或成外星人，千变万化不模板，不改观点不塞词，排版润色可分离。处理完和你原文的质量还在一个层次。润色排版引擎，适合小说、自媒体文章、文案。润色（降AI味）不…

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
77
Run on models
none yet
Process rating
D
49/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Write Bash

Files scanned: 4. 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")
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "display_name_en"
  • note frontmatter-key unknown frontmatter key "description_zh"
  • note frontmatter-key unknown frontmatter key "description_en"

Process rating: all ten parameters 49/100

  • 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
  • 40Consistency. Frontmatter name (wenzi-runse) differs from the folder (runse-skill)
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 30 steps
  • 100Execution cost. Instruction body is 584 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 2 example trigger phrases
  • +3Description length 321: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
The skill is a real cloud text-polishing tool, but it has review-worthy risks around broad automatic triggering, sending user text to a remote service, AI-detection-evasion marketing, and plaintext API-key persistence.
LLM: suspicious (high) · 5 Sept 2026