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BF humanize-mba-text

去除中文文本中的 AI 生成痕迹，使其更符合中国 MBA 毕业论文的自然写作风格。当用户提到"去 AI 痕迹"、"去除 AI 写作痕迹"、"MBA 论文改写"、"让这段文字更像人写的"、"去除机器感"等关键词时触发。适用于需要降低文本 AI 特征、提升学术写作自然度的场景。

ClawHub Agent Skills author: Big Stephen v1.5.0 MIT-0 51 files body ≈ 1 834 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

去除中文文本中的 AI 生成痕迹，使其更符合中国 MBA 毕业论文的自然写作风格。当用户提到"去 AI 痕迹"、"去除 AI 写作痕迹"、"MBA 论文改写"、"让这段文字更像人写的"、"去除机器感"等关键词时触发。适用于需要降低文本 AI 特征、提升学术写作自然度的场景。

As a process F 36/100 · Will not run — References files that are not bundled: references/rules/categories/*.toml, scripts/rule_loader.iter_regex_categories, references/rules/**/*.toml

ProcedureResearchtype 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
F
36/100
Will not run
References files that are not bundled: references/rules/categories/*.toml, scripts/rule_loader.iter_regex_categories, references/rules/**/*.toml
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 51. 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")
  • warning missing-ref reference to a missing file: references/rules/categories/*.toml
  • warning missing-ref reference to a missing file: scripts/rule_loader.iter_regex_categories
  • warning missing-ref reference to a missing file: references/rules/**/*.toml

Process rating: all ten parameters 36/100

Will not run. References files that are not bundled: references/rules/categories/*.toml, scripts/rule_loader.iter_regex_categories, references/rules/**/*.toml
  • 0Tools and files. 3 referenced file(s) missing: references/rules/categories/*.toml, scripts/rule_loader.iter_regex_categories, references/rules/**/*.toml
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (humanize-mba-text) differs from the folder (humanize-mba-text-skill)
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 55 steps
  • 100Execution cost. Instruction body is 1834 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
  • -32 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 137: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 55 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (7 of 10)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.

External checks

ClawHub: suspicious
The skill does not look like malware, but it is explicitly built to reduce AI-detection and plagiarism-check signals in MBA thesis text.
LLM: suspicious (high) · VirusTotal: · 10 Jul 2026