$npx -y skills add lishix520/academic-paper-skills --skill strategistSystematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) de
| 1 | # Academic Paper Strategist |
| 2 | |
| 3 | ## Overview |
| 4 | |
| 5 | This skill provides a systematic framework for strategic planning of academic papers in philosophy and interdisciplinary research. It guides you through three phases—from platform selection to optimized outline—with AI-driven literature search, research gap identification, originality assessment, and quality-controlled outline design. |
| 6 | |
| 7 | **Output**: A detailed, review-ready paper outline with supporting documentation (platform style guide, literature review, gap analysis, reviewer assessment). |
| 8 | |
| 9 | **Companion Skill**: Use **academic-paper-composer** to execute the outline and write the full paper. |
| 10 | |
| 11 | --- |
| 12 | |
| 13 | ## When to Use This Skill |
| 14 | |
| 15 | Use **academic-paper-strategist** when you need to: |
| 16 | |
| 17 | **Planning Stage**: |
| 18 | - Design a research paper from initial idea to structured outline |
| 19 | - Identify a suitable publication platform (PhilArchive, arXiv, etc.) |
| 20 | - Understand writing standards for a specific preprint platform |
| 21 | |
| 22 | **Research Stage**: |
| 23 | - Conduct systematic literature search |
| 24 | - Identify research gaps with evidence |
| 25 | - Assess originality of your research idea |
| 26 | - Predict potential impact |
| 27 | |
| 28 | **Design Stage**: |
| 29 | - Structure paper chapters and arguments |
| 30 | - Optimize outline from reviewer perspective |
| 31 | - Prepare submission-ready strategy |
| 32 | |
| 33 | **Triggers**: |
| 34 | - "Plan a paper on [topic]" |
| 35 | - "Help me design a paper about [subject]" |
| 36 | - "Identify research gaps in [field]" |
| 37 | - "Is this idea original?" |
| 38 | - "What platform should I submit to?" |
| 39 | |
| 40 | --- |
| 41 | |
| 42 | ## Workflow Overview |
| 43 | |
| 44 | ``` |
| 45 | Phase 1: PLATFORM ANALYSIS (Target Selection + Style Learning) |
| 46 | ↓ |
| 47 | Phase 2: THEORETICAL FRAMEWORK (AI-Driven Gap Identification) |
| 48 | ↓ |
| 49 | Phase 3: OUTLINE OPTIMIZATION (Quality-Controlled Design) |
| 50 | ↓ |
| 51 | Output: Detailed Outline + Supporting Documentation |
| 52 | ``` |
| 53 | |
| 54 | **Quality Gates**: 3 validation checkpoints ensure each phase meets standards before proceeding. |
| 55 | |
| 56 | --- |
| 57 | |
| 58 | ## Phase 1: Platform Analysis |
| 59 | |
| 60 | ### Goal |
| 61 | Identify the optimal submission platform and understand its writing standards through systematic sample paper analysis. |
| 62 | |
| 63 | ### Input Required from User |
| 64 | - **Core research idea or topic** (brief description) |
| 65 | - **Target platform** (optional - if unclear, I'll recommend) |
| 66 | - **Field/discipline** (philosophy, cognitive science, interdisciplinary, etc.) |
| 67 | |
| 68 | ### Workflow |
| 69 | |
| 70 | #### Step 1.1: Platform Selection (If Needed) |
| 71 | |
| 72 | If target platform unclear, I will: |
| 73 | |
| 74 | 1. **List candidate platforms** based on research content: |
| 75 | - **PhilArchive/PhilPapers**: Philosophy papers, phenomenology, metaphysics |
| 76 | - **arXiv (cs.AI, q-bio.NC)**: Computational, neuroscience, AI-related |
| 77 | - **PhilSci-Archive**: Philosophy of science, formal methods |
| 78 | - **PsyArXiv**: Psychology, cognitive science |
| 79 | - **SocArXiv**: Social sciences, interdisciplinary |
| 80 | |
| 81 | 2. **Evaluate each platform**: |
| 82 | - Subject area alignment (does your topic fit?) |
| 83 | - Methodology match (philosophical/empirical/computational) |
| 84 | - Acceptance criteria |
| 85 | - Typical review timeline |
| 86 | |
| 87 | 3. **Provide recommendation** with reasoning |
| 88 | |
| 89 | 4. **Decision Point 1**: You confirm platform or suggest alternative |
| 90 | |
| 91 | #### Step 1.2: Sample Paper Search (AI-Driven, Quality-Controlled) |
| 92 | |
| 93 | I will conduct **multi-dimensional search** for 8-10 representative papers: |
| 94 | |
| 95 | **Search Strategy** (load `references/search_strategy.md` for details): |
| 96 | |
| 97 | **Time Dimension**: |
| 98 | - Recent (last 6 months): 3 papers - capture current trends |
| 99 | - Current (1-2 years): 3 papers - established standards |
| 100 | - Classic (highly cited): 2 papers - quality benchmarks |
| 101 | |
| 102 | **Relevance Dimension**: |
| 103 | - Use keyword combinations from your topic |
| 104 | - Score each paper 0-10 for relevance |
| 105 | - Retain only papers scoring ≥7/10 |
| 106 | |
| 107 | **Diversity Dimension**: |
| 108 | - Multiple authors (≥5 unique) |
| 109 | - Different research perspectives |
| 110 | - Varied paper lengths |
| 111 | |
| 112 | **Tools Used**: |
| 113 | - Exa MCP (semantic search) |
| 114 | - Tavily MCP (web search) |
| 115 | - Platform-specific search (PhilPapers, arXiv) |
| 116 | |
| 117 | **Quality Validation**: |
| 118 | After search, I'll run `scripts/evaluate_samples.py` to generate |