StrategistSAFE

Systematic framework for planning and writing academic papers using Claude Code. Includes strategist (planning) and composer (writing) skills with quality checkpoints.

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: academic-paper-strategist
description: Systematic 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) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints. Output: optimized detailed outline ready for systematic writing (use with academic-paper-composer skill).
---

# Academic Paper Strategist

## Overview

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.

**Output**: A detailed, review-ready paper outline with supporting documentation (platform style guide, literature review, gap analysis, reviewer assessment).

**Companion Skill**: Use **academic-paper-composer** to execute the outline and write the full paper.

---

## When to Use This Skill

Use **academic-paper-strategist** when you need to:

**Planning Stage**:
- Design a research paper from initial idea to structured outline
- Identify a suitable publication platform (PhilArchive, arXiv, etc.)
- Understand writing standards for a specific preprint platform

**Research Stage**:
- Conduct systematic literature search
- Identify research gaps with evidence
- Assess originality of your research idea
- Predict potential impact

**Design Stage**:
- Structure paper chapters and arguments
- Optimize outline from reviewer perspective
- Prepare submission-ready strategy

**Triggers**:
- "Plan a paper on [topic]"
- "Help me design a paper about [subject]"
- "Identify research gaps in [field]"
- "Is this idea original?"
- "What platform should I submit to?"

---

## Workflow Overview

```
Phase 1: PLATFORM ANALYSIS (Target Selection + Style Learning)
    ↓
Phase 2: THEORETICAL FRAMEWORK (AI-Driven Gap Identification)
    ↓
Phase 3: OUTLINE OPTIMIZATION (Quality-Controlled Design)
    ↓
Output: Detailed Outline + Supporting Documentation
```

**Quality Gates**: 3 validation checkpoints ensure each phase meets standards before proceeding.

---

## Phase 1: Platform Analysis

### Goal
Identify the optimal submission platform and understand its writing standards through systematic sample paper analysis.

### Input Required from User
- **Core research idea or topic** (brief description)
- **Target platform** (optional - if unclear, I'll recommend)
- **Field/discipline** (philosophy, cognitive science, interdisciplinary, etc.)

### Workflow

#### Step 1.1: Platform Selection (If Needed)

If target platform unclear, I will:

1. **List candidate platforms** based on research content:
   - **PhilArchive/PhilPapers**: Philosophy papers, phenomenology, metaphysics
   - **arXiv (cs.AI, q-bio.NC)**: Computational, neuroscience, AI-related
   - **PhilSci-Archive**: Philosophy of science, formal methods
   - **PsyArXiv**: Psychology, cognitive science
   - **SocArXiv**: Social sciences, interdisciplinary

2. **Evaluate each platform**:
   - Subject area alignment (does your topic fit?)
   - Methodology match (philosophical/empirical/computational)
   - Acceptance criteria
   - Typical review timeline

3. **Provide recommendation** with reasoning

4. **Decision Point 1**: You confirm platform or suggest alternative

#### Step 1.2: Sample Paper Search (AI-Driven, Quality-Controlled)

I will conduct **multi-dimensional search** for 8-10 representative papers:

**Search Strategy** (load `references/search_strategy.md` for details):

**Time Dimension**:
- Recent (last 6 months): 3 papers - capture current trends
- Current (1-2 years): 3 papers - established standards
- Classic (highly cited): 2 papers - quality benchmarks

**Relevance Dimension**:
- Use keyword combinations from your topic
- Score each paper 0-10 for relevance
- Retain only papers scoring ≥7/10

**Diversity Dimension**:
- Multiple authors (≥5 unique)
- Different research perspectives
- Varied paper lengths

**Tools Used**:
- Exa MCP (semantic search)
- Tavily MCP (web search)
- Platform-specific search (PhilPapers, arXiv)

**Quality Validation**:
After search, I'll run `scripts/evaluate_samples.py` to generate evaluation report:
```bash
python scripts/evaluate_samples.py
```

This produces:
- Sample quality metrics
- Time distribution check
- Relevance statistics
- Diversity assessment
- Pass/Fail recommendation

**Quality Gate 1** (Must Pass):
- ✓ Sample papers ≥8
- ✓ Time distribution balanced
- ✓ Average relevance ≥8/10
- ✓ Unique authors ≥5

**If Failed**: Re-search with adjusted criteria

#### Step 1.3: Writing Standards Extraction

From the 8-10 sample papers, I will extract:

**Structural Patterns**:
- Abstract structure (Problem→Method→Results→Contribution?)
- Chapter organization (how many sections? typical flow?)
- Average proportions (Intro 15%, Main 70%, Conclusion 15%?)

**Style Patterns**:
- First-person vs passive voice usage
- How arguments are structured
- Citation density and format
- Use of technical terminology

**Format Specifications**:
- Typical word count range
- Reference count range
- Section heading conventions

**Output**: `[Platform]_Writing_Standards_Guide.md`

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.