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npx skills add reason-machines/codex-skills --skill academic-research-skills-codex
AI-assisted academic research workflows for literature review, paper writing, peer review, and research pipelines
npx skills add reason-machines/codex-skills --skill academic-research-skills-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.
Academic Research Skills (ARS) for Codex provides five core workflows:
Install using the Codex skill installer with git method:
After installation, open a new Codex conversation to activate the skill.
You should see one entry: academic-research-suite. You should NOT see separate entries for academic-paper, deep-research, etc.
Use $academic-research-suite followed by your research task:
The Codex adapter automatically routes to the appropriate workflow based on your request.
| Workflow | When to Use | Example Trigger |
|---|---|---|
deep-research | Need research question refinement, literature review, fact-checking | "conduct a systematic review on..." |
academic-paper | Need paper outline, drafting, citations, revision | "write a research paper about..." |
academic-paper-reviewer | Need manuscript review, peer review simulation | "review this research manuscript..." |
academic-pipeline | Need full research-to-publication workflow | "run end-to-end pipeline from topic to paper" |
experiment-agent | Need code experiment design, study protocols | "plan a reproducible code experiment..." |
For best results, provide goal, current state, and constraints:
Codex emulates Claude Code /ars-* commands as aliases:
| Alias | Workflow | Purpose |
|---|---|---|
ars-plan | academic-paper | Create paper plan/structure |
ars-outline | academic-paper | Generate outline only |
ars-abstract | academic-paper | Draft abstract |
ars-lit-review | academic-paper | Build literature review |
ars-citation-check | academic-paper | Verify citations |
ars-disclosure | academic-paper | Generate AI disclosure statement |
ars-format-convert | academic-paper | Convert between formats |
ars-revision-coach | academic-paper | Get revision guidance |
ars-revision | academic-paper | Execute revisions |
ars-full | academic-pipeline | Run full pipeline |
Either prefix style works:
Or if your client supports it:
When you have a broad topic but no clear research question:
Expected: ARS asks narrowing questions before producing an outline.
For checkpoint-based workflow:
For cross-model verification (optional):
Without these, ARS runs entirely within Codex/OpenAI. Cross-model review uses Anthropic API when explicitly requested.
ARS tracks research artifacts through "Material Passports" - metadata files that follow:
Reset Material Passport by starting a new Codex conversation.
Expected output:
For guidance without executing changes:
If /skills doesn't show academic-research-suite:
ls -la "$HOME/.codex/skills/academic-research-suite"If you see academic-paper, deep-research, etc. as separate skills:
If ARS routes to the wrong workflow, be more explicit:
Or use specific alias:
When citations cannot be verified:
ars-citation-check mode with source files attachedThese warnings are non-blocking:
[features].codex_hooks is deprecated - update Codex config when convenienthooks need review before they can run - ARS Codex doesn't require hooks for normal useTest routing without full execution:
Expected: Route to deep-research socratic mode.
This Codex package differs from the original Claude Code ARS:
| Feature | Claude Code | Codex Package |
|---|---|---|
| Installation | Plugin marketplace | Git-based skill installer |
| Commands | Native /ars-* slash commands | Emulated aliases via router |
| Agent teams | Automatic background agents | Inline unless explicitly delegated |
| Hooks | SessionStart, SubagentStop | Vendored for traceability only |
| Cross-model review | GPT/Gemini secondary dispatch | Anthropic Claude API (explicit config) |
| Updates | Marketplace auto-update | Manual reinstall |
1d0c8625207c9cd8fc46132b1ef930f2cc012236skills/academic-research-suite/ars/docs/SETUP.mdskills/academic-research-suite/ars/docs/ARCHITECTURE.mdFor issues specific to the Codex packaging, open an issue at the Codex package repository. For ARS workflow issues, consult the original Claude Code repository.
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/skillsUse $academic-research-suite to help me plan a systematic literature review on
AI adoption in higher education quality assurance.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 audienceUse $academic-research-suite: ars-plan my paper on AI governance/ars-plan my paper on AI governanceUse $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.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 introUse $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]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.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 checklistexport ARS_CROSS_MODEL=claude-opus-4.7
export ANTHROPIC_API_KEY=your_api_key_here{
"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"
}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.Use $academic-research-suite: ars-lit-review
Topic: AI ethics in higher education
Scope: 2020-2026, peer-reviewed only
Output: thematic synthesis with citation matrixUse $academic-research-suite: ars-format-convert
Input: [attach paper.md]
From: Markdown
To: LaTeX (IEEE conference template)
Preserve: citations, figures, tablesUse $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 statementUse $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.
Do not rewrite yet - provide plan only.Use $academic-research-suite: ars-revision
[attach draft.md and reviewer_comments.txt]
Execute revisions based on Reviewer 2 methodology concerns.
Track changes: show original -> revised for each section.
Update Material Passport with revision metadata.# Remove all ARS skills
rm -rf "$HOME/.codex/skills/academic-"*
rm -rf "$HOME/.codex/skills/deep-research"
rm -rf "$HOME/.codex/skills/experiment-agent"
# Reinstall single 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 gitUse $academic-research-suite deep-research workflow in socratic mode.
[your request]Use $academic-research-suite: ars-outline
[your request]Use $academic-research-suite academic-pipeline workflow.
Stage 0: Intake and dashboard
STOP and show dashboard for approval
[After approval]
Stage 1: Research question refinement via Socratic dialogue
STOP and show refined question
[Continue stage by stage]Use $academic-research-suite deep-research workflow.
Search strategy: parallel tracks
Track 1: Scopus, Web of Science - quantitative studies
Track 2: Google Scholar - grey literature, policy docs
Track 3: Specialized databases - ERIC, ProQuest Education
Synthesize results into single literature matrix.Use $academic-research-suite academic-paper-reviewer workflow.
Pass 1: Structure and contribution (desk-reject check)
[Wait for my review]
Pass 2: Methodology rigor
[Wait for my review]
Pass 3: Citation integrity and ethics
[Final decision]Use $academic-research-suite: ars-citation-check
Citation library: Zotero export attached (bibtex format)
Paper: [attach draft.md]
Cross-check all in-text citations against Zotero library.
Flag missing entries and formatting errors.Use $academic-research-suite experiment-agent workflow.
Existing analysis: [attach analysis.py, results.csv]
Task: Create reproducible experiment protocol around this analysis
Output: protocol.md, requirements.txt, reproduction checklistUse $academic-research-suite: ars-format-convert
Input: [attach paper.md]
Template: University PhD thesis LaTeX template [attach template.tex]
Preserve: custom environments for theorems, university citation stylecodex exec --ephemeral --sandbox read-only \
-C /path/to/academic-research-skills-codex \
'Use $academic-research-suite. Router smoke test only. Classify workflow and mode for: I want to write a paper on AI adoption but do not have a research question yet.'