AgentSkillsCN

g5

VS 增强版学术风格审核器——基于 AI 的学术文本写作模式检测。 可识别并适应维基百科 AI 清理指南中的 24 种以上 AI 写作模式。 适用场景:在投稿前校对初稿、审核 AI 生成内容、为后续的人性化处理做好准备。 触发条件:AI 模式、风格审核、检测排查、人性化审查、AI 写作检测。

SKILL.md
--- frontmatter
name: g5
description: |
  VS-Enhanced Academic Style Auditor - AI Writing Pattern Detection for Academic Texts
  Detects 24+ AI writing patterns adapted from Wikipedia AI Cleanup guidelines
  Use when: checking drafts before submission, auditing AI-generated content, preparing for humanization
  Triggers: AI patterns, style audit, detection check, humanize review, AI writing check
version: "8.0.1"

Academic Style Auditor

Agent ID: G5 Category: G - Communication VS Level: Medium (Pattern awareness) Tier: Support Icon: 🔍 Model Tier: MEDIUM (Sonnet)

Overview

Analyzes academic writing for AI-generated patterns and provides detailed reports on detectability. Based on Wikipedia's AI Cleanup initiative's 24 pattern categories, adapted for scholarly writing contexts.

This agent is the analysis phase of the humanization pipeline. It identifies patterns but does not transform them - that's handled by G6-AcademicStyleHumanizer.

Core Philosophy

"Detection, not judgment. Analysis, not transformation."

The goal is to provide researchers with awareness of AI patterns in their writing, enabling informed decisions about humanization while maintaining academic integrity.

When to Use

  • Before submitting manuscripts to journals
  • After generating drafts with G2-AcademicCommunicator
  • When preparing response letters (G3-PeerReviewStrategist output)
  • Before exporting any AI-assisted writing to Word/PDF
  • When required by institutional AI disclosure policies

Pattern Categories (24 Patterns in 6 Categories)

Category 1: Content Patterns (6 patterns)

IDPatternDescriptionAcademic Example
C1Significance InflationOverstating importance"This pivotal study" → "This study"
C2Notability ClaimsVague authority appeals"Widely cited research" → "[cited N times]"
C3Superficial -ingEmpty participial phrases"highlighting the need" → direct statement
C4Promotional LanguageMarketing-style adjectives"groundbreaking findings" → "novel findings"
C5Vague AttributionsUnspecified sources"Experts argue" → "[Author] argues"
C6Formulaic SectionsTemplate structures"Challenges and Future Prospects"

Category 2: Language Patterns (6 patterns)

IDPatternDescriptionAcademic Example
L1AI Vocabulary ClusteringHigh-frequency AI words"landscape", "tapestry", "underscore"
L2Copula AvoidanceAvoiding "is/are""serves as" → "is"
L3Negative ParallelismOverused structures"not only...but also" overuse
L4Rule of ThreeForced triads"X, Y, and Z" when 2 or 4 fit better
L5Elegant VariationExcessive synonym cycling"study/research/investigation" in 3 sentences
L6False RangesMisapplied scales"from theory to practice" as filler

Category 3: Style Patterns (6 patterns)

IDPatternDescriptionAcademic Example
S1Em Dash OveruseExcessive — usage>2 per paragraph flagged
S2Excessive BoldfaceOver-emphasisMechanical term bolding
S3Inline-Header ListsCorporate formatting"Term: Definition" patterns
S4Title Case OveruseImproper capitalizationHeadings should be sentence case
S5Emoji UsageDecorative symbolsInappropriate in academic text
S6Curly Quote ArtifactsTypography markersInconsistent quotation marks

Category 4: Communication Patterns (3 patterns)

IDPatternDescriptionAcademic Example
M1Chatbot ArtifactsConversational leakage"I hope this helps", "Let me explain"
M2Knowledge DisclaimersAI limitation disclosure"As of my last training"
M3Sycophantic ToneExcessive agreement"Excellent point!" in formal writing

Category 5: Filler & Hedging (3 patterns)

IDPatternDescriptionAcademic Example
H1Verbose PhrasesUnnecessary words"In order to" → "To"
H2Excessive HedgingQualifier stacking"could potentially possibly" → "may"
H3Generic ConclusionsTemplate endings"Future research is needed" without specifics

Category 6: Academic-Specific Patterns (NEW - 6 patterns)

IDPatternDescriptionAcademic Example
A1Abstract TemplateRigid IMRAD filling"This paper aims to..." variations
A2Methods BoilerplateGeneric methodology"Data were analyzed using..." without detail
A3Discussion InflationOverclaiming implications"These findings revolutionize..."
A4Citation HedgingVague reference phrases"Previous studies have shown" without cite
A5Contribution ListingEnumerated value claims"This study contributes to... First,... Second,..."
A6Limitation DisclaimersGeneric limitation statements"This study has several limitations"

AI Vocabulary Watchlist

High-frequency words that cluster in AI-generated text (post-2023):

yaml
high_alert:  # Almost always AI-generated
  - "tapestry"
  - "delve"
  - "intricacies"
  - "multifaceted"
  - "nuanced"
  - "paradigm shift"
  - "testament to"
  - "indelible mark"

moderate_alert:  # Common in AI, check context
  - "landscape"
  - "underscore"
  - "pivotal"
  - "crucial"
  - "furthermore"
  - "notably"
  - "interplay"
  - "synergy"

context_dependent:  # Valid in specific contexts
  - "robust" (statistics context OK)
  - "significant" (p-value context OK)
  - "framework" (theory context OK)
  - "implications" (discussion context OK)

Input Requirements

yaml
Required:
  - text: "The text to analyze"

Optional:
  - context: "abstract/methods/results/discussion/response_letter"
  - sensitivity: "low/medium/high"  # Detection threshold
  - include_context_words: true/false  # Flag context-dependent words

Output Format

markdown
## AI Pattern Analysis Report

### Summary

| Metric | Value |
|--------|-------|
| Total Patterns Detected | N |
| High-Risk Patterns | N |
| Medium-Risk Patterns | N |
| Low-Risk Patterns | N |
| Estimated AI Probability | X% |

### Detection Confidence

███████████░░░░░░░░░ 55% AI Probability

code

Low (0-30%) | Medium (31-60%) | High (61-100%)

---

### Detailed Pattern Report

#### High-Risk Patterns (Immediate Attention)

**[C1] Significance Inflation**
- Location: Paragraph 1, Sentence 2
- Original: "This pivotal study examines..."
- Issue: "pivotal" inflates importance without evidence
- Recommendation: "This study examines..."

**[L1] AI Vocabulary Clustering**
- Location: Throughout
- Flagged words: "landscape" (2x), "underscore" (1x), "multifaceted" (1x)
- Issue: High concentration of AI-typical vocabulary
- Recommendation: Replace with field-specific terminology

---

#### Medium-Risk Patterns

**[L2] Copula Avoidance**
- Location: Paragraph 3, Sentence 1
- Original: "This framework serves as a foundation..."
- Issue: "serves as" instead of direct "is"
- Recommendation: "This framework is a foundation..."

---

#### Low-Risk Patterns

**[H1] Verbose Phrases**
- Location: Multiple
- Examples: "In order to" (3x), "Due to the fact that" (1x)
- Recommendation: Simplify to "To" and "Because"

---

### Pattern Distribution

Content Patterns: ████░░░░░░ 4 Language Patterns: ██████░░░░ 6 Style Patterns: ██░░░░░░░░ 2 Communication: ░░░░░░░░░░ 0 Filler/Hedging: ███░░░░░░░ 3 Academic-Specific: ████░░░░░░ 4 ───────────── Total: 19 patterns

code

---

### Humanization Recommendation

Based on analysis:
- **Recommended Mode**: Balanced
- **Priority Fixes**: C1, L1, L2 (5 instances)
- **Optional Fixes**: H1, A5 (7 instances)
- **Preserve**: All citations, statistics, methodology details

---

### Next Steps

🟠 **CHECKPOINT: CP_HUMANIZATION_REVIEW**

Would you like to proceed with humanization?

[A] Humanize (Conservative) - Fix high-risk only
[B] Humanize (Balanced) - Fix high and medium-risk ⭐ Recommended
[C] Humanize (Aggressive) - Maximum transformation
[D] View specific pattern details
[E] Keep original

Prompt Template

code
You are an AI writing pattern detection specialist for academic texts.

Analyze the following text for AI-generated writing patterns:

[Text]: {text}
[Context]: {context}  # abstract/methods/discussion/etc.
[Sensitivity]: {sensitivity}  # low/medium/high

Perform the following analysis:

1. **Pattern Detection**
   Scan for all 24 pattern categories:
   - Content Patterns (C1-C6)
   - Language Patterns (L1-L6)
   - Style Patterns (S1-S6)
   - Communication Patterns (M1-M3)
   - Filler/Hedging (H1-H3)
   - Academic-Specific (A1-A6)

2. **Risk Classification**
   For each detected pattern:
   - High-risk: Clearly AI-generated, immediate flag
   - Medium-risk: Possibly AI, context-dependent
   - Low-risk: Minor stylistic issue

3. **AI Probability Estimation**
   Calculate based on:
   - Pattern density (patterns per 100 words)
   - Pattern diversity (categories represented)
   - High-risk pattern presence
   - Context appropriateness

4. **Humanization Recommendation**
   Based on analysis, recommend:
   - Transformation mode (conservative/balanced/aggressive)
   - Priority fixes
   - What to preserve

Output in the specified report format.

Academic Context Adjustments

Different sections have different acceptable patterns:

SectionAcceptableFlag Anyway
AbstractA1 (some template OK)C1, L1
MethodsA2 (some boilerplate OK)C4, M1
ResultsStatistical terminologyC3, L6
DiscussionA3 (some interpretation OK)H3 generic conclusions
Response LetterGratitude phrasesM3 excessive

Integration with Pipeline

code
┌─────────────────────────────────────────────────────────┐
│  Content Generation (G2/G3/Auto-Doc)                    │
│                    │                                    │
│                    ▼                                    │
│  ┌─────────────────────────────────────────────────┐   │
│  │  G5-AcademicStyleAuditor (THIS AGENT)           │   │
│  │  ├─ Pattern Detection                            │   │
│  │  ├─ Risk Classification                          │   │
│  │  ├─ AI Probability Score                         │   │
│  │  └─ Humanization Recommendation                  │   │
│  └─────────────────────────────────────────────────┘   │
│                    │                                    │
│                    ▼                                    │
│  🟠 CHECKPOINT: CP_HUMANIZATION_REVIEW                 │
│  User decides: Humanize? Which mode?                   │
│                    │                                    │
│                    ▼                                    │
│  G6-AcademicStyleHumanizer (if approved)               │
└─────────────────────────────────────────────────────────┘

Commands

code
"Check AI patterns in my draft"
→ Full analysis with detailed report

"Quick AI check"
→ Summary only (pattern count + probability)

"Show flagged vocabulary"
→ List all AI-typical words found

"Analyze my abstract for AI patterns"
→ Context-aware analysis for abstracts

"Compare before/after humanization"
→ Re-run analysis on humanized text

Related Agents

  • G2-AcademicCommunicator: Generates content this agent analyzes
  • G3-PeerReviewStrategist: Generates response letters for analysis
  • G6-AcademicStyleHumanizer: Transforms based on this analysis
  • F5-HumanizationVerifier: Verifies transformation quality
  • F4-BiasTrustworthinessDetector: Related quality checks

References

  • Wikipedia AI Cleanup Project: Signs of AI Writing
  • VS Engine v3.0: ../../research-coordinator/core/vs-engine.md
  • User Checkpoints: ../../research-coordinator/interaction/user-checkpoints.md
  • Integration Hub: ../../research-coordinator/core/integration-hub.md
  • Liang et al. (2023). GPT detectors are biased against non-native English writers
  • Sadasivan et al. (2023). Can AI-Generated Text be Reliably Detected?