Academic Research Skills Codex

Academic Research Skills for Codex

Skill by ara.so — Codex Skills collection.

This skill provides a comprehensive suite of AI-assisted academic research workflows including deep research, paper writing, peer review, and end-to-end research pipelines. Originally designed for Claude Code, this Codex-native package routes requests to specialized research agents based on user intent.

What It Does

Academic Research Skills (ARS) for Codex provides five core workflows:

1. Deep Research - Literature reviews, systematic reviews, research question refinement, fact-checking
2. Academic Paper - Outlining, drafting, citation formatting, revision, AI disclosure
3. Academic Paper Reviewer - Manuscript review, simulated peer review, editorial decisions
4. Academic Pipeline - End-to-end research-to-publication workflow with integrity gates
5. Experiment Agent - Code experiment planning, study protocols, reproducibility validation

Installation

Install using the Codex skill installer with git method:

python "$HOME/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py" \
  --repo Imbad0202/academic-research-skills-codex \
  --ref main \
  --path skills/academic-research-suite \
  --method git

Update Existing Installation

rm -rf "$HOME/.codex/skills/academic-research-suite"
python "$HOME/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py" \
  --repo Imbad0202/academic-research-skills-codex \
  --ref main \
  --path skills/academic-research-suite \
  --method git

After installation, open a new Codex conversation to activate the skill.

Verify Installation

/skills

You should see one entry: academic-research-suite. You should NOT see separate entries for academic-paper, deep-research, etc.

Core Usage Patterns

Basic Invocation

Use $academic-research-suite followed by your research task:

Use $academic-research-suite to help me plan a systematic literature review on
AI adoption in higher education quality assurance.

The Codex adapter automatically routes to the appropriate workflow based on your request.

Workflow Selection

Structured Request Pattern

For best results, provide goal, current state, and constraints:

Use $academic-research-suite.

Goal: write a journal article on AI in higher education QA
Current materials: literature matrix and rough findings, no outline yet
Output needed: paper architecture and evidence checklist
Constraints: English, APA 7, policy audience

Command Aliases

Codex emulates Claude Code /ars-* commands as aliases:

Using Aliases

Either prefix style works:

Use $academic-research-suite: ars-plan my paper on AI governance

Or if your client supports it:

/ars-plan my paper on AI governance

Workflow Examples

Deep Research: Socratic Question Refinement

When you have a broad topic but no clear research question:

Use $academic-research-suite.

I want to write about AI adoption in higher education quality assurance.
I don't have a clear research question yet.
Use Socratic dialogue to help me narrow the question first.

Expected: ARS asks narrowing questions before producing an outline.

Academic Paper: From Notes to Draft

Use $academic-research-suite.

Task: Turn these research notes into an IMRaD paper.
Materials: [attach notes.md, data_summary.csv]
Target: 6000-8000 words, APA 7, submit to Higher Education Research
Output: Full outline with section word counts, then draft intro

Paper Review: Simulated Peer Review

Use $academic-research-suite to review this manuscript.

Mode: full review
Focus: methodology, contribution, citation integrity, desk-reject risks
Output: reviewer reports + editorial decision letter

[attach manuscript.pdf or manuscript.md]

Academic Pipeline: Staged Execution

For checkpoint-based workflow:

Use $academic-research-suite to start an academic-pipeline run.

Begin with Stage 0 intake and stop after producing the pipeline dashboard.
Wait for my approval before Stage 1.

Experiment Agent: Reproducible Study Design

Use $academic-research-suite experiment-agent.

Plan a code experiment comparing three ML models on education dataset.
Requirements: reproducible, statistical rigor, version control, artifact storage
Output: experiment protocol + reproducibility checklist

Configuration

Environment Variables

For cross-model verification (optional):

export ARS_CROSS_MODEL=claude-opus-4.7
export ANTHROPIC_API_KEY=your_api_key_here

Without these, ARS runs entirely within Codex/OpenAI. Cross-model review uses Anthropic API when explicitly requested.

Material Passport

ARS tracks research artifacts through "Material Passports" - metadata files that follow:

{
  "artifact_id": "paper_v1_outline",
  "created": "2026-05-17T10:30:00Z",
  "workflow": "academic-paper",
  "stage": "outline",
  "integrity_checks": ["citation_format", "structure"],
  "sources": ["source1.pdf", "source2.pdf"],
  "status": "approved"
}

Reset Material Passport by starting a new Codex conversation.

Working with Citations

Citation Check

Use $academic-research-suite: ars-citation-check

[paste paper text with citations]

Verify all citations are formatted correctly in APA 7.
Flag any unverifiable sources.

Expected output:

• Citation format compliance report
• Unverifiable citations flagged
• Suggested corrections

Literature Review Mode

Use $academic-research-suite: ars-lit-review

Topic: AI ethics in higher education
Scope: 2020-2026, peer-reviewed only
Output: thematic synthesis with citation matrix

Paper Formatting and Conversion

Format Conversion

Use $academic-research-suite: ars-format-convert

Input: [attach paper.md]
From: Markdown
To: LaTeX (IEEE conference template)
Preserve: citations, figures, tables

AI Disclosure Statement

Use $academic-research-suite: ars-disclosure

Paper stage: final draft before submission
AI tools used: Codex for literature search, outline generation, citation formatting
Human contribution: research design, analysis, interpretation, revision
Output: journal-ready disclosure statement

Revision Workflow

Revision Coach

For guidance without executing changes:

Use $academic-research-suite: ars-revision-coach

[attach draft.md and reviewer_comments.txt]

Analyze reviewer feedback and suggest revision strategy.
Prioritize major vs minor revisions.