Academic paper writing is traditionally a human-driven, iterative, and often subjective process. This repo takes a different approach by formalizing paper planning and writing as a programmable pipeline using Claude Code skills. It introduces a structured two-phase framework with rigorous quality checkpoints enforced by Python scripts, bringing a level of automation and consistency to academic manuscript development that is rare in this domain.
what the academic paper skills framework does
At its core, this project provides two specialized Claude Code skills: a strategist and a composer, designed to guide the academic paper workflow from initial planning through to manuscript completion. The strategist skill focuses on the early stages — analyzing target preprint platforms (like PhilArchive, arXiv, and PhilSci-Archive), conducting literature reviews, identifying research gaps with evidence, and optimizing outlines via an elaborate reviewer simulation.
The reviewer simulation is a standout feature: it evaluates outlines across 7 dimensions, each scored on 5 points, totaling a 35-point rubric. Only outlines that score 28 or above proceed to the writing phase. This scoring simulates a high-level peer review, automating a traditionally manual and subjective step.
Once an outline passes, the composer skill takes over. It systematically writes the paper chapter-by-chapter, validating each section and running final manuscript assessments before completion. This phase is also guarded by Python verification scripts that enforce quality standards at defined gates, ensuring consistency and adherence to platform-specific style learned from 8-10 sample papers.
The framework is tailored primarily for philosophers and interdisciplinary researchers, reflecting the domain-specific challenges of publishing on platforms with rigorous standards. The emphasis on 3-5 citations backing every identified research gap also underscores a commitment to evidence-based research practices.
architectural strengths and design tradeoffs
What distinguishes this repo is how it encodes academic quality assurance as a programmable pipeline rather than a purely human judgment process. The use of Claude Code skills modularizes the workflow into discrete, reusable steps, each with clear inputs, outputs, and validation criteria.
The 7-dimension, 35-point reviewer simulation is an interesting tradeoff. It abstracts peer review into a quantifiable rubric, which is both a strength and a limitation. While it provides consistent, automated feedback, it inevitably simplifies nuanced academic evaluation. However, the repo mitigates this by enforcing relatively high thresholds (28/35) and backing gap identifications with 3-5 citations, anchoring automation to evidence.
The Python verification scripts add another layer of rigor, programmatically gating transitions between phases. This reduces human error and enforces discipline but also means users must be comfortable running Python alongside Claude Code.
Under the hood, the repo leverages platform style learning from sample papers, enabling it to tailor outputs to different preprint venues. This is a practical touch that improves the relevance and acceptance likelihood of the generated manuscripts.
The main tradeoff here is domain specificity. The framework is designed with philosophy and interdisciplinary research in mind, targeting specific preprint platforms. Adapting it to other academic domains or journals would likely require significant re-training of style extraction and rubric adjustment.
quick start with academic-paper-skills
installation
Prerequisites:
- Claude Code installed and configured
- Python 3.8+ (for running verification scripts)
Setup steps:
git clone https://github.com/yourusername/academic-paper-skills.git
cp -r strategist ~/.claude/skills/academic-paper-strategist
cp -r composer ~/.claude/skills/academic-paper-composer
Restart Claude Code to load the new skills.
usage examples
Planning a paper with the strategist skill:
You: Plan a paper on how mortality generates consciousness
Claude: [Activates academic-paper-strategist]
Let me guide you through the three phases...
Writing from an approved outline with the composer skill:
You: Write the paper from this outline: [your outline]
Claude: [Activates academic-paper-composer]
Starting Phase 1: Foundation setup...
This interaction shows how the repo turns academic writing into a guided conversation with Claude, backed by structural quality gates.
verdict
This repo provides a compelling approach to formalizing academic writing as a multi-phase, quality-checked pipeline using Claude Code skills and Python verification scripts. Its strength lies in combining structured outline evaluation with automated, platform-tailored writing phases, all rigorously gated.
It’s particularly relevant for researchers in philosophy and interdisciplinary fields publishing on preprint platforms like PhilArchive or arXiv. The approach demands some comfort with Claude Code and Python scripting, and its domain-specific design means it may not directly translate to other academic disciplines without adaptation.
The tradeoff between automation and nuanced academic judgment is clear: the 35-point rubric simplifies peer review but enforces consistency and evidence-backed gap identification. For those who want a programmable, reproducible academic writing workflow with built-in quality assurance, this repo is worth exploring. However, users should be aware that it does not replace human peer review but rather formalizes and automates early-stage quality control to improve draft readiness.
In production, this means fewer dead-end drafts and a more disciplined writing process, which can be a real time saver for academics balancing research with teaching and other duties.
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→ GitHub Repo: lishix520/academic-paper-skills ⭐ 666 · Python