https://github.com/scdenney/open-science-skills
A library of Agentic Skills for Claude Code and LLM agents, codified from social science standards and methodological texts for doing experimental and other kinds of work.
https://github.com/scdenney/open-science-skills
anthropic claude-code claude-code-skills conjoint experimental-research fair list-experiment literature-review manuscript-qa methods-reporting open-science peer-review pre-registration social-science survey-experiments text-classification topic-modeling
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A library of Agentic Skills for Claude Code and LLM agents, codified from social science standards and methodological texts for doing experimental and other kinds of work.
- Host: GitHub
- URL: https://github.com/scdenney/open-science-skills
- Owner: scdenney
- License: other
- Created: 2026-01-21T17:14:13.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2026-06-26T10:03:55.000Z (12 days ago)
- Last Synced: 2026-06-26T11:09:09.374Z (12 days ago)
- Topics: anthropic, claude-code, claude-code-skills, conjoint, experimental-research, fair, list-experiment, literature-review, manuscript-qa, methods-reporting, open-science, peer-review, pre-registration, social-science, survey-experiments, text-classification, topic-modeling
- Language: Markdown
- Homepage:
- Size: 5.52 MB
- Stars: 22
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-claude-skills - scdenney/open-science-skills
- awesome-academic-skills - open-science-skills - by [scdenney](https://github.com/scdenney) · `NOASSERTION`.<br>Social-science methods suite from real methodological texts: conjoint design/cleaning/diagnostics, list-experiments, cross-national design, methods-reporting, FAIR/figure-table audits. Source-grounded; broad, so audit individual skills. (Suites, Systems & Meta / Discipline-Specific Packs)
README
# Open Science Skills
[](https://code.claude.com/docs/en/skills)
[](codex/README.md)
[](https://github.com/scdenney/open-science-skills/releases)
[](LICENSE)
[](#skills)
[](https://github.com/scdenney/open-science-skills/commits/main)
[](SOURCES.md)
[](#contributing)
Reusable agent workflows for experimental social science, computational text analysis, manuscript QA, and transparent reporting. The same research methods are packaged natively for both Claude Code and OpenAI Codex.
| Platform | Package | Invoke |
|---|---|---|
| [Claude Code](https://code.claude.com/docs/en/skills) | 35 skills in the [`oss` plugin](plugin/skills) | `/oss:skill-name` |
| [OpenAI Codex](https://developers.openai.com/codex/skills) | 34 skills in the [`codex/` library](codex/README.md) | `$skill-name` |
The two libraries track each other closely. On the Codex side there is no `presubmit`.
This is the toolkit I use in my own research. It is built from a curated corpus of methodology texts and grows as I add new sources, ideas, and skills. Authoring and editing are mine, with help from Opus 4.8, Gemini 3.0, and ChatGPT 5.4.
Both libraries follow the official authoring guidance for [Claude Code](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/best-practices) and [Codex](https://developers.openai.com/codex/skills): procedural workflows over definitions, with trigger-rich descriptions and progressive disclosure. The methods stay aligned across platforms; only invocation and tooling adapt to each runtime.
> These skills support the research and writing process. They do not replace it. They follow APSA, JARS, DA-RT, TOP, and FAIR open-science expectations, and all guidance is grounded in 150+ published sources and documented workflow patterns. See [**SOURCES.md**](SOURCES.md) for the full bibliography.
---
## Contents
[Skill Map](#skill-map) · [How Skills Work](#how-skills-work) · [Installation](#installation) · [Skills](#skills) · [Contributing](#contributing) · [License](#license)
**Skills:** [Project Setup](#project-setup) · [Ideation](#ideation) · [Research Design](#research-design) · [Analysis](#analysis) · [Corpus Processing](#corpus-processing) · [Writing & Reporting](#writing--reporting) · [Figures & Tables](#figures--tables) · [Manuscript QA](#manuscript-qa) · [Review & Submission](#review--submission)
---
## Skill Map
```mermaid
flowchart LR
A[Research Design] --> B[Analysis]
A --> C[Writing and PAP]
B --> D[Methods Reporting]
C --> D
D --> E[Manuscript QA and FAIR]
E --> F[Review and Submission]
G[Ideation] --> A
G --> C
A -.-> A1[conjoint / survey / list / cross-national]
B -.-> B1[topic modeling / text classification / council voting / model committee / calibration / OCR + OCR eval]
C -.-> C1[hypotheses / literature review / narrative / preregistration]
D -.-> D1[figures / tables / methods reporting]
E -.-> E1[FAIR / citations / fact-check / figure-table-audit / replication-package / archive checks]
F -.-> F1[paper-tex / paper-review-lite / paper-review-lite-codex / presubmit / journal-review]
G -.-> G1[diverge / diverge-codex / fable-orchestrate or 46-orchestrate]
```
Use the domain skills when designing or analyzing a study. Use the manuscript-QA skills when a draft exists and you need to check whether FAIR availability, citations, figures, tables, reporting, and replication materials can survive review.
---
## How Skills Work
Invocation depends on the platform:
| Platform | Implicit | Explicit | Source |
|---|---|---|---|
| Claude Code | Loads matching skills from prompt context | `/oss:skill-name` | [`plugin/skills/`](plugin/skills) |
| Codex | Loads matching skills from their descriptions | `$skill-name` | [`codex/`](codex) |
Orchestration and delegated-review variants require explicit invocation because they start subagents or external model calls.
---
## Installation
### Claude Code
#### Option 1 — Plugin (recommended, installs all skills + slash commands)
**Permanent install** (user-wide, persists across all projects):
```bash
# Step 1: Register the marketplace (one-time)
claude plugin marketplace add scdenney/open-science-skills
# Step 2: Install the plugin
claude plugin install oss@open-science-skills
# Project-only install
claude plugin install oss@open-science-skills --scope project
```
The plugin's slash-command prefix is `oss:` (short for **o**pen **s**cience **s**kills). The marketplace and GitHub repo are still named `open-science-skills`.
**Session-only** (no install required, active for the current session):
```bash
git clone https://github.com/scdenney/open-science-skills.git
cd open-science-skills && claude --plugin-dir ./plugin
```
All 35 skills auto-trigger based on your prompts. All 35 slash commands (`/oss:research-repo`, `/oss:conjoint-design`, `/oss:fair-check`, `/oss:figures`, `/oss:tables`, `/oss:paper-tex`, `/oss:figure-table-audit`, `/oss:replication-package`, and so on) are immediately available. The prefix can be omitted when no other installed plugin claims the same name.
Option 2 — Selective install (choose specific skills, auto-trigger only)
Use the interactive install script to pick only the skills you want:
```bash
git clone https://github.com/scdenney/open-science-skills.git
cd open-science-skills
bash plugin/scripts/install.sh
```
The script lists available skills and lets you choose interactively. Skills are installed to `./.claude/skills/` by default (current project only). Options:
```bash
# Install to user-wide skills directory (all projects)
bash plugin/scripts/install.sh --target ~/.claude/skills
# Install specific skills non-interactively
bash plugin/scripts/install.sh --skill conjoint-design survey-design list-experiment
# Install all skills
bash plugin/scripts/install.sh --all --target ~/.claude/skills
```
Restart Claude Code after installing to load the new skills.
Option 3 — Manual copy (single skill, auto-trigger only)
```bash
git clone https://github.com/scdenney/open-science-skills.git
# Project-level (current project only) — copy the whole skill folder:
# many skills ship reference/, assets/, or scripts/ files their SKILL.md points at
mkdir -p your-project/.claude/skills
cp -R open-science-skills/plugin/skills/conjoint-design \
your-project/.claude/skills/
# User-wide (all projects)
mkdir -p ~/.claude/skills
cp -R open-science-skills/plugin/skills/list-experiment ~/.claude/skills/
```
> **Note:** Manual install gives you auto-trigger only. Slash commands (`/skill-name`) require the plugin.
### Codex
Codex discovers repository skills under `.agents/skills` and user-wide skills under `~/.agents/skills`. From the repository root, install all 34 native skills user-wide:
```bash
mkdir -p "$HOME/.agents/skills"
for skill in "$PWD"/codex/*/; do
ln -sfn "${skill%/}" "$HOME/.agents/skills/$(basename "$skill")"
done
```
For selective and repository-scoped installation, plus the compact Codex catalog, see [`codex/README.md`](codex/README.md).
---
## Skills
The detailed catalog shows Claude Code commands by default. Platform-specific entries are labeled: **Codex** means a Codex-native skill, while **Claude Code → Codex** means a Claude Code skill that calls Codex. Unmarked research workflows also have counterparts in the [Codex catalog](codex/README.md), except for `presubmit`.
### Project Setup
Skill
Invoke
What it does
research-repo
/research-repo
Scaffold or audit a research project repository organized around its source library. For a new repo, build the sources/{og,md,unprocessed} + references.bib spine (PDF to Markdown via OpenDataLoader PDF), a process-source intake command, CLAUDE.md/AGENTS.md, .gitignore, and the archetype-appropriate analysis/manuscript/review folders, then smoke-test the pipeline; for an existing repo, audit against the convention with detection recipes for orphan PDFs, bib drift, and naming. Pairs with process-source (per-PDF intake) and replication-package (publication output).
### Workflow & Orchestration
Skill
Invoke
What it does
fable-orchestrate
Claude Code
/fable-orchestrate
Multi-model orchestration with Fable 5 as tech lead. Routes reasoning-heavy work to a deep-reasoner subagent (Opus), mechanical work to a fast-worker subagent (Sonnet), and fresh-perspective or high-stakes work to Codex, a different-vendor GPT-5 peer. High-stakes tasks run Opus and Codex in parallel, then synthesize. Ships the two agent definitions and a codex-peer.sh driver.
46-orchestrate
Codex
$46-orchestrate
Sol-led Codex orchestration for complex work. Routes bounded research, implementation, and verification to role-based subagents; uses blind parallel review for high-blast-radius work that is difficult to verify; and keeps planning, integration, and final accountability with the lead.
### Ideation
Skill
Invoke
What it does
diverge
/diverge
Brainstorm-then-select: before implementing, generate 3–5 conceptually distinct approaches labeled by creativity dimension ([Novel], [Surprising], [Diverse], [Conventional]) and hold for selection. Resists defaulting to the most obvious solution. After Creative Preference Optimization (Ismayilzada et al., 2025).
diverge-codex
Claude Code → Codex
/diverge-codex
Cross-model variant of diverge. Delegates the brainstorm to Codex (GPT-5.4) via codex exec, presents its approaches for selection, then has Codex implement the chosen one. A second model family widens the space of approaches.
### Research Design
Skill
Invoke
What it does
conjoint-design
/conjoint-design
Attribute architecture, AMCE/AMIE estimation, power analysis (cjpowR), BART heterogeneity detection, design variants
conjoint-diagnostics
/conjoint-diagnostics
Diagnostic checklist: design, estimation, measurement error (IRR), external validity, interpretation
conjoint-cleaning
/conjoint-cleaning
Qualtrics export to analysis-ready format: column conventions, reshaping, choice mapping, translation, pilot detection, validation
survey-design
/survey-design
Question construction, scale design, survey flow, pretesting, respondent burden, social desirability mitigation
cross-national-design
/cross-national-design
Cross-national survey experiments: per-country power, sensitivity bias auditing, instrument localization
list-experiment
/list-experiment
Item count technique: pre-design sensitivity assessment, control list design, NLSreg/MLreg estimation, assumption testing, placebo diagnostics
### Analysis
Skill
Invoke
What it does
topic-modeling
/topic-modeling
STM with metadata covariates, topic count selection via coherence-exclusivity diagnostics, reporting
text-classification
/text-classification
LLM-based classification: codebook design, learning regime selection, human-LLM hybrid workflows, validation
model-council-voting
/model-council-voting
Panel of models as independent coders: consensus rules, chance-corrected agreement (Cohen/Fleiss/Krippendorff), correlated-error diagnostics, validation beyond the panel
model-committee
Claude Code + Codex
/model-committee
$model-committee
GPT-5.5 and Claude Opus 4.8 as a deliberative committee: use-case gate, blind proposals, cross-critique and revision, blinded cross-ranking, and a precommitted rule for one decision
llm-calibration-logprobs
/llm-calibration-logprobs
Within-model confidence from token log-probabilities: aggregation, triage, calibration (ECE, Brier, reliability diagrams) against human ground truth
### Corpus Processing
Skill
Invoke
What it does
vlm-ocr-pipeline
/vlm-ocr-pipeline
VLM-based OCR: model selection, image handling, prompt engineering, batch strategy, accuracy evaluation, reproducibility
post-ocr-cleanup
/post-ocr-cleanup
Post-OCR cleanup: LLM and rule-based correction, quality diagnostics, multilingual considerations, corpus-level QA, provenance
vlm-ocr-evaluation
/vlm-ocr-evaluation
Compare OCR systems before bulk runs: candidate set, stratified ground truth, CER/WER with declared normalization, per-language and per-stratum accuracy
### Writing & Reporting
Skill
Invoke
What it does
hypothesis-building
/hypothesis-building
Falsifiability, counterfactuals, DAGs, FPCI, three-level hypothesis specification, equivalence testing, SESOI
literature-review
/literature-review
Evidence maps, closest-prior-work assessment, gap verdicts, literature clusters, synthesis plans
narrative-building
/narrative-building
Introduction logic, literature reviews, the "Why-to-If-Then" funnel, cumulative framing, multi-experiment coherence
pre-registration-writing
/pre-registration-writing
PAP structure, registry selection, analytical strategy specification, code pre-registration, deviation documentation
methods-reporting
/methods-reporting
40-item reporting checklist: CONSORT standards, JARS preregistration elements, DA-RT transparency
paper-tex
/paper-tex
Typeset a working paper or journal submission in house-style LaTeX from any draft (Markdown, Word, TeX, ODT, HTML): pandoc conversion, EB Garamond template, \figcap title+note captions, [H] floats, single-spaced title block with the introduction on its own page, and journal-specific prep (spacing, page limit, anonymization, disclosures). Bundles a tested convert-and-build driver.
### Figures & Tables
Skill
Invoke
What it does
figures
/figures
Design publication-quality figures: chart choice from comparison, scales, color, legend ordering matched to visual order, self-contained captions, reproducibility
tables
/tables
Design publication-quality tables: column order matching the argument, row grouping, precision and uncertainty conventions, self-contained titles and notes, code-generated workflows
### Manuscript QA
Skill
Invoke
What it does
fair-check
/fair-check
FAIR audit for completed manuscripts: data/code/material availability, repository metadata, persistent identifiers, licenses, access restrictions, reuse conditions
citation-check
/citation-check
In-text/reference parity, DOI and source-status checks, fabrication/existence verification (Crossref/OpenAlex), stale working papers, citation-style and support audits
fact-check
/fact-check
Verify each in-text claim is actually supported by its cited source. Runs citation-check first, then locates each source's knowledge-base Markdown (sources/md/) and audits claim support, overclaiming, direction, scope, and misattribution. Pairs with process-source.
figure-table-audit
/figure-table-audit
End-stage QA of the finished figure/table set: inventory, cross-references, text-to-table consistency, accessibility, SI and replication linkage. Pairs with figures and tables (production-stage).
replication-package
/replication-package
Scaffold or audit a replication package at a target directory. Generates folder structure, README, master.R, figure/table crosswalk, codebook template, LICENSE placeholder, .gitignore, and a pre-release checklist. Platform-neutral (Harvard Dataverse, OSF, Zenodo, GitHub releases). Adapted from Yusaku Horiuchi's replication-package-guide with FAIR-principle integration. Pair with fair-check.
### Review & Submission
Skill
Invoke
What it does
paper-review-lite
/paper-review-lite
Critical-Reviewer-style pre-submission audit. Parallel quote-grounded sub-agents, verification cross-check, CONSORT and pre-reg audit for experimental papers. Single-model, in-session counterpart to the standalone presubmit CLI.
paper-review-lite-codex
Claude Code → Codex
/paper-review-lite-codex
Cross-model adversarial variant of paper-review-lite. Claude and Codex (GPT-5.4) independently apply the same review specification, then each cross-checks the other's findings; surviving issues are annotated by confidence (mutual, asymmetric-confirmed, single-model-adjudicated). Roughly 22 model calls. Use before submission for maximum pressure and a second model family's blind spots.
presubmit
/presubmit
Activator and setup wizard for the standalone presubmit Python CLI. Walks first-time users through install (venv + pip install -e .), Anthropic API key setup, and output location, then runs the heavier 30+ stage adversarial pipeline (resumable, cost-tracked, optional --math and --code-dir add-ons). Heavier API-driven counterpart to paper-review-lite.
journal-review
/journal-review
Drafts a senior-peer referee report on someone else's manuscript for a social-science journal. Five parallel finder sub-agents (Breaker, Butcher, Shredder, Void, Situator), a Blue Team filter, Chief Reviewer synthesis, and Tone Guard sanitization produce a 1,200–2,000-word report (Recommendation, Summary, Major Concerns, Additional Concerns, Suggestions for Revision). Different role from paper-review-lite and presubmit, which are calibrated for self-audit. This one acts as a third-party referee and is meant to support, not replace, your own assessment of a manuscript.
---
## Contributing
PRs welcome. To add a new skill:
1. Create `plugin/skills//SKILL.md` following the [skill authoring best practices](https://platform.claude.com/docs/en/agents-and-tools/agent-skills/best-practices)
2. Add `plugin/commands/.md` (see existing examples — one paragraph activation prompt + `$ARGUMENTS`)
3. Add the Codex-native package at `codex//` with `SKILL.md` and `agents/openai.yaml`, unless the workflow is intentionally platform-specific
4. Add sources to `SOURCES.md` under a new or existing section
5. Update the platform catalogs and badges
6. Run `bash plugin/scripts/check.sh` and validate each changed Codex skill before opening a PR
## License
This project is licensed under [Creative Commons Attribution-NonCommercial 4.0 International](LICENSE). The skills are intended for noncommercial scholarly and educational use.
The `citation-check`, `literature-review`, `figures`, `tables`, and `figure-table-audit` skills remix workflow ideas from [Cheng-I Wu's Academic Research Skills for Claude Code](https://github.com/Imbad0202/academic-research-skills), also licensed CC BY-NC 4.0. The instructions here are rewritten for this repository's open-science and experimental-social-science scope.
The `replication-package` skill adapts the structural conventions in [Yusaku Horiuchi's replication-package-guide](https://github.com/yhoriuchi/replication-package-guide) (the source for single-entry-point, compact vs. build/analyze layouts, figure/table crosswalk, paper-consistency check, correction workflow, and pre-release checklist). FAIR-principle integration and Claude Code/Codex skill packaging are added on top; Harvard Dataverse and other platform-specific upload mechanics are not included. Cite Horiuchi's guide if you publish a package built with this skill.